Citation
Traditional and commercial farm supply response in agricultural development

Material Information

Title:
Traditional and commercial farm supply response in agricultural development : the case for basic grains in Guatemala
Creator:
Alvarez, Jose, 1940- ( Dissertant )
Andrew, C. D. ( Thesis advisor )
Polopolus, Leo ( Reviewer )
Ward, R. M. ( Reviewer )
McPherson, W. W. ( Woodrow Wilson ) ( Reviewer )
Carvajal, M. J. ( Reviewer )
Fry, Jack L. ( Degree grantor )
Place of Publication:
Gainesville, Fla.
Publisher:
University of Florida
Publication Date:
Copyright Date:
1977
Language:
English
Physical Description:
xviii, 211 leaves : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Agriculture ( jstor )
Commercial production ( jstor )
Commercials ( jstor )
Crops ( jstor )
Farmers ( jstor )
Farms ( jstor )
Grains ( jstor )
Market prices ( jstor )
Marketing ( jstor )
Prices ( jstor )
Agriculture -- Economic aspects -- Guatemala ( lcsh )
Dissertations, Academic -- Food and Resource Economics -- UF
Food and Resource Economics thesis Ph. D
Grain trade -- Guatemala ( lcsh )
City of Gainesville ( local )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Abstract:
A growing population with about two-thirds employed in agriculture, a limited arable land base, and poverty stricken farmers experiencing unemployment and low levels of food production are characteristics that portray Guatemala as a developing country. The nation's development efforts focus on the implementation of programs designed to alleviate those detrimental characteristics. Program objectives at the Institute of Agricultural Science and Technology ( I CTA) of Guatemala intend to develop new technologies designed to generate productivity increases especially for basic grains in the traditional farm sector. These programs will enable the country to augment supply without expanding the area committed to production. Two types of problems, however, may result from productivity advances. Small farmers could use the new technology to produce the A growing population with about two-thirds employed in agriculture, a limited arable land base, and poverty stricken farmers experiencing unemployment and low levels of food production are characteristics that portray Guatemala as a developing country. The nation's development efforts focus on the implementation of programs designed to alleviate those detrimental characteristics. Program objectives at the Institute of Agricultural Science and Technology ( I CTA) of Guatemala intend to develop new technologies designed to generate productivity increases especially for basic grains in the traditional farm sector. These programs will enable the country to augment supply without expanding the area committed to production. Two types of problems, however, may result from productivity advances. Small farmers could use the new technology to produce the Total production differs among enterprises witii respect to yields and product distribution. Variations in cash sales are the result of differences in farm demand for production and consumption purposes; the more traditional the crop, the lower will be sales. The results of the regression equations support the conceptual model; in general, the estimated coefficients behave as hypothesized. Traditional crops generally appear at near zero income and farm size levels while commercial crops are cultivated when higher levels of income and farm size have been attained. Elasticities of market supply for traditional and commercial crops are high at low levels of income and farm size. However, while commercial crops still show some responsiveness at higher income and farm size levels, the traditional crop response becomes almost perfectly inelastic. This behavior is the result of farmers becoming involved in the activities of the market economy once self-sufficiency has been secured, and shifting into commercial crop production at higher levels of income and farm size. Thus, since traditional crops pervade the basic grains production system in Guatemalan agriculture, little hope prevails for the attainment of massive increases in supply of basic grains. Although corn in regions three and four and rice in regions four and five seem to have a slight potential for increased production, the resulting increases would fall far behind the goal of the Guatemalan government.
Thesis:
Thesis--University of Florida.
Bibliography:
Bibliography: leaves 200-210.
Additional Physical Form:
Also available on World Wide Web
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Jose Alvarez.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
020564977 ( ALEPH )
03386412 ( OCLC )
AAB3889 ( NOTIS )

Downloads

This item has the following downloads:


Full Text









TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE
IIN AGRICULTURAL DEVELOPMENT:
THE CASE FOR BASIC GRAINS III GUATEMALA












By

Jose Alvarez


A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY





UNIVERSITY OF FLORIDA


1977


















A los pequeRos agricultores del Altiplano Central que conocr durante

mi breve estadia en Guatemala:

-A los que perecieron a consecuencia del terremoto del 4 de

Febrero de 1976, como sencillo tribute a su laboriosidad y

hospitalidad;

-A los sobrevivientes de la cat5strofe, con la esperaiza de

que el future les depare la prosperiJad que nunca han tenido

y que tanto merecen.

A la nostalgia que produce la imposibilidad de hacer esta

investigacio'n sobre los guajiros de mi Cuba,pero compensado

por haberla hecho por los de ese pedazo de America por el que

Jose Mart sintico especial devoci6n.


















To the small farmers of the Central Highlands I met during my short

stay in Guatemala:

-To those who died because of the earthquake on February 4th,

1976, as a humble tribute to their diligence and hospitality;

-To the survivors of that catastrophe, hoping that the future

will bring them the prosperity they have never had and so much

deserve.

To the nostalgic feeling produced by the impossibility of conducting

this research on the guajiros of my Cuba, but compensated for having

done it on those from that part of Latin America for which Jose Mart'

felt special devotion.













AC K!-'OWLE DCGIME TS


In most cases, every research product is the result of multiple

endeavors. This one is no exception. Sinceits very beginning, many

persons and institutions have provided enormous contributions. With-

out them this dissertation would never have been possible. The list

is long as deep is my indebtedness.

Special thanks go to every member of my Supervisory Committee:

To Chris 0. Andrew, my chairman, for his help, patience, and encourage-

ment not only during every phase of this research but throughout all

these years of graduate work; to Ronald W. Ward for always being

available to share his knowledge of Econometrics and for his valuable

comments; to W.W. McPherson, who taught me the theoretical background

of Economic Development, for providing his experience in the area

through sound remarks; to Manuel J. Carvajal for his help in this

dissertation and his availability during all these years; to Leo

Polopolus, Department Chairman, for his support, his comments and the

financial assistance of the Department.

My appreciation to the Institute of Agricultural Science and

Technology (ICTA) of Guatemala, particularly to Mario Martinez and

Astolfo Fumagalli, for the enthusiasm shown in approving the research








topic. Special thanks to my friends in Socioeconomra-ICTA, starting

with the Coordinator, Peter E. Hildebrand. His vast experience with

the Guatemalan situation materialized in helpful comments and ideas

during several reviews of the manuscript. To Pete and Joyce, his

wife, thanks also for their hospitality and understanding.

I am grateful to the Rockefeller Foundation,especially to Joe

D. Black, for willingness to finance the original project. And to

International Programs-IFAS, University of Florida, for making some

funds available at an early stage of the research.

The Concejo Nacional de Planificaci6n Econ6mica de Cuatemala

deserves credit for authorizing use of the Farm Policy Analysis data

utilized in this study. Russell Misheloff, Daniel A. Chaij, Robert

Bartram, and James Riordan, USAID-Wlashington, facilitated release of

the tapes and Carl D. Koone, USAID-Guatemala, was a most valuable

intermediary.

My appreciation to Sheriar Irani and Mario Ariet for writing and

debugging so many computer programs. The facilities of the Northeast

Regional Data Center of the State University System of Florida were

used for making all computations.

Special thanks to Beth Davis and Ann Ritch for valuable assistance

in typing so many drafts and to Beth Davis again for typing the final

copy.

Finally, and above all, I want to thank my wife, Mercy, for her

love and encouragement in both good and difficult times. She and I

owe too much to hario and Nini Ariet and want to thank them for being

always there.














TABLE OF CONTENTS


Page

ACKNOWLEDGMENTS . . . ... . . . . . . iv

LIST OF TABLES. . . . . . . . . . . x

LIST OF FIGURES . . . ... . . . . . . xiv

ABSTRACT. . . . . . . .. . . . xvi

CHAPTER

I INTRODUCTION . . . . . . . . . 1

Setting of the Study . . . . .. .
Physical Environment . . . . .
Population . . . . . . . 2
Government and Political Subdivisions. 3
The Economy. . . . . . . 5
Agriculture. . . . . . ... 6
Markets and Marketing. . . . . 7
Foreign Trade. . . . . . . 8
Setting of the Problem .. . ... . 10
introduction . . . . . . 10
Problem Statement. . . . . . 15
Objectivesof the Study ........ . 25
Data Source and Data Considerations . .. 25
Relevance of the Project ........ 31
Organization of the Dissertation. ... . 32

II A;J EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT 33

Agriculture and Economic Development. . 33
Agriculture in LDCs: A Changing
Spectrum of Priorities . . . 34
Agriculture versus industry: A False
Issue. .. .. .. .. ..... . 36
The Role of Agriculture in Economic
Development. .......... . 37
Some Prescriptions for Agricultural
Development . . . . . 39








CHAPTER Page

Marketing and Economic Development . . 42
Marketing Defined . . . . ... .42
The Role of Marketing in the Economy. 43
The Role of Marketing in Economic
Development . . . . .. ..44
Marketing and the Theory of Demand in
LDCs. . . . . . . . . 50
Marketing and the Theory of Supply in
LDCs. . . . . . . . . 52

III THEORETICAL AND METHODOLOGICAL FRAMEWORK FOR
INVESTIGATING TRADITIONAL AND COMMERCIAL FARM
SUPPLY RESPONSE . . . . . . ... .56

Basic Economic System of the Guatemalan 56
Small Farmer . . . . . . .
Method of Estimation . . . . ... 64
Hypotheses. . . . . . . ... 64
The Model . . . . . . .. 66
Adaptation of the Model . . ... 69
Production and Distribution Activities . 70
Data Used and Implications . . . ... 70
Summary. . . . . . . . . ... 72

IV PRODUCTION AND DISTRIBUTION ACTIVITIES. ... . 73

The Input Market . . . . . ... .73
Seed Utilization. . . . . ... 73
Urea Application. . . . . ... 78
Soil Additives. . . . . . ... 80
Other Chemicals . . . . ... .80
Other Fertilizers . . . . ... .80
Pesticides. . . . . . . ... 81
Labor . . . . . . . ... .81
The Product Market . . . . . ... 82
Total Production. . . . . .. 82
Animal Feed and Seed. . . . ... 82
Family Consumption. . . . . ... 87
Processing. . . . . . . ... 87
Rent Payments . . . . . . 88
Sales "in Kind" . . . . . .. 88
Donations . . . . . .... . 88
Total Losses. . . . . . ... 88
Cash Sales. . . . . . . ... 89
Marketing Expenditures. . . . ... 89
Summary. . . . . . . . . ... 90








CHAPTER Page

V TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE. 93

Associations .............. 93
Regression Coefficients. . . ... 06
Income-Quantity Relationships. ... 108
Farm Size-Quantity Relationships . 109
Price-Quantity Relationships . . . 109
Corn. .................. .. 109
Regression Coefficients . . . . 110
Income-Quantity Relationships. ... 114
Farm Size-Quantity Relationships . 114
Price-Quantity Relationships .. . 115
Beans . . . . . . . . . 116
Regression Coefficients. . . . .. 116
Income-Quantity Relationships. ... 118
Farm Size-Quantity Relationships . 118
Price-Quantity Relationships .. ... 19
Sorghum . . . . . . . . . 119
Regression Coefficients. . . . .. 119
Income-Quantity Relationships. . . 120
Farm Size-Quantity Relationships .. 120
Price-Quantity Relationships . . . 120
Rice. . . . . . . . . . 121
Regression Coefficients. . . . .. 121
Income-Quantity Relationships. . . 124
Farm Size-Quantity Relationships .... 124
Price-Quantity Relationships . . . 124
Wheat . . . . . . . ... .. 126
Regression Coefficients . . . .. 126
Income-Quantity Relationshps . . . 128
Farm Size-Quantity Relationships . . 129
Price-Quantity Relationships . . . 129
Summary . . . . . . . . . 129

VI SUMMARY, CONCLUSIONS, IMPLICATIONS AND RECOMMEN-
DATIOINS. . . . . . . . . . . 131

Problem and Objectives. . . . . .. 131
Research Findings . . . . . . 133
Production and Distribution Activities 134
Traditional and Commercial Farm Supply
Response . ..*. . . . . . 135
Data Generzalizations and Implications . 137
Errors and Omissions in Data Recording 138
Upward or Downward Bias . . 139


viii








CHAPTER Page


Education of household head. ... 140
Distance to the market ...... 140
Total farm size. .. . . . . 140
Total family income. . . . .. 141
Farmgate price . . . . . 141
Quantity demanded on the farm. .. 142
Relative profitability ratio . . 142
Conclusions and Recommendations .... 143

VII REFLECTIONS ON THE THEORY OF DEVELOPMENT. ... . 147

Introduction . . . . . . . . 147
The Green Revolution: Generation Problems
and Small Farm Development . . .... ... 149
First Generation. . . . .. . 149
Second Generation . . . . .. 152
Third Generation ......... . 153
Suggestions for Further Researcn . . . .. 155
Epilog . . . . . . . . . . 156

GLOSSARY. . . . . .. . . . . . . 158

APPEINDIX. . . . . . . . . . .. 161

List of Crops. . . . . ... . . 161
The Mathematical Model ........ .. 161
The Statistical Model: Its Assumptions and
Possible Violations. . . . . ... 172
The Regression Model . . . .. 172
Possible Violations of the Assumptions. 173
Normality. . . . ... .. .. 173
Zero mean. . . . . . ... 174
Homoskedasticity . . . . . 174
Sufficient observations. . . ... 175
No multicollinearity . . . . 175
Regression Results. . . . . ... 177

REFERENCES. . . . . .. . . . . . . 200

BIOGRAPHICAL SKETCH . . . . . . . . . . 211












LIST OF TABLES


Table Page


I Guatemala's imports and exports of cereals,
1963-72 . . . . . . . . . 9

2 Guatemala's agricultural imports and exports,
total imports and exports, and agricultural
percentage of total, 1963-72 . . . . ... II

3 Average wholesale prices for beans and corn, in
Guatemala City, 1972 . . . . . . ... .20

4 Average wholesale prices for beans and corn, in
Guatemala City, 1973 . . . ... . .. . 21

5 Average wholesale prices for beans and corn, in
Guatemala City, 1974 . . . ... .. .... .22

6 Number of sampled farms by region and farm size. 28

7 Number of sampled farms by region, sub-region,
and department . . . . ... .. .... .29

8 Total inputs used in basic grain production by
regions of Guatemala . . . . .. . . 74

9 Relative importance of inputs used in basic grain
production by regions of Guatemala . . ... 76

10 Seed purchase and sale proportions relative to
total production and total seed use. . . . 79

II Distribution of total basic grain production by
regions of Guatemala . . . . . . . 83

12 Relative importance of the distribution of total
basic grain production by regions of Guatemala . 85

13 Marketing expenditures as a percent of average
price received by enterprises and regions. ... 91







LIST OF TABLES--continued


Table Page


14 Regression coefficients for each basic grain or
association by regions of Guatemala. . . . 94

15 Sign and significance level of the regression
coefficients for each basic grain or association
by regions of Guatemala. . . . . . ... 96

16 Income elasticities of market supply for each
basic grain or association by regions of
Guatemala. . . . . . . . . . . 97

17 Area elasticities of market supply for each basic
grain or association by regions of Guatemala . 99

18 Price elasticities of market supply for each basic
grain or association by regions of Guatemala . 101

A-l The price variable: descriptive statistics for
each of the estimated equations. . . . ... 163

A-2 The education variable: descriptive statistics
for each of the estimated equations. . . .. .164

A-3 The total farm size variable: descriptive statis-
tics for each of the estimated equations .... .165

A-4 The distance to market variable: descriptive
statistics for each of the estimated equations 166

A-5 The quantity demanded on the farm variable: de-
scriptive statistics for each of the estimated
equations . . . . . . . . . 167

A-6 The relative profitability ratio variable:
descriptive statistics for each of the estimated
equations . . . . . . . . . 168

A-7 The total income variable: descriptive statis-
tics for each of the estimated equations . . 169

A-8 RI corn-beans: simple correlation coefficients
matrix of the independent variables. . . .. 178








LIST OF TABLES--continued


Table Page


A-9 R corn-beans: simple correlation coefficients
matrix of the independent variables. . . .. .178

A-10 P6 corn-beans: simple correlation coefficients
matrix of the independent variables. . . .. 179

A- I R6 corn-sorghum: simple correlation coefficients
matrix of the independent variables . . .. 179

A-12 R, corn-beans-sorghum: simple correlation coef-
ficients matrix of the independent variables . 180

A-13 R corn: simple correlation coefficients matrix
of the independent variables . . . . . 180

A-14 R, corn: simple correlation coefficients matrix
o? the independent variables . . . . ... 81

A-15 R corn: simple correlation coefficients matrix
or the independent variables . . . . . 181

A-16 R corn: simple correlation coefficients matrix
o the independent variables . . . . . 182

A-17 R corn: simple correlation coefficients matrix
of the independent variables . . . . . 182

A-18 R beans: simple correlation coefficients matrix
of the independent variables . . . . . 183

A-19 R beans: simple correlation coefficients matrix
o the independent variables . . . . . 183

A-20 R beans: simple correlation coefficients matrix
of the independent variables . . . . . 184

A-21 R sorghum: simple correlation coefficients matrix
ot the independent variables . . . . ... . 184

A-22 R rice: simple correlation coefficients matrix of
the independent variables. . . . . . . 185

A-23 R rice: simple correlation coefficients matrix of
the independent variables . . . . . . 185

xii








LIST OF TABLES--continued


Table Page


A-24 R rice: simple correlation coefficients matrix
o the independent variables . . . . .. 186

A-25 R wheat: simple correlation coefficients matrix
od the independent variables. . . . . . 186

A-26 R wheat: simple correlation coefficients matrix
oJ the independent variables . . . . .. 187

A-27 Regression coefficients for each basic grain or
association by regions of Guatemala ...... 188

A-28 Income-quantity relationships for the associations
graphed in Figure 8 . . . . . . . 190

A-29 Farm size-quantity relationships for the associa-
tions graphed in Figure 9 . . . . . . 191

A-30 Price-quantity relationships for the associations
graphed in Figure 10. . . . . . . ... 192

A-31 Income-quantity relationships for corn graphed in
Figure 11 . . . . . . . . .. . 193

A-32 Farm size-quanty relationships for corn graphed
in Figure 12. . . . . . . . . 194

A-33 Price-quantity relationships for corn graphed in
Figure 13 . . . . . . . .. .. . 195

A-34 Income-quantity relationships for beans graphed
in Figure 14. . . . . . . . . 196

A-35 Income-quantity relationships for rice graphed
in Figure 15. ................ . 197

A-36 Farm size-quantity relationships for rice
graphed in Figure 16. . . . . . . ... 198

A-37 Farm size-quantity relationships for wheat
graphed in Figure 17. . . . . . . ... 199


xiii













LIST OF FIGURES


Figure Page


S Political divisions and transportation routes of
Guatemala. . . . . . . . . . 4

2 Average wholesale prices for yellow and white
corn in Guatemala City, 1972-74. . . . 19

3 Average wholesale prices for black, white, and
red beans, in Guatemala City, 1972-74. . . .. 23

4 Important crops in the different regions of
Guatemala. . . . . . . . . . 27

5 Guatemalan small farmer consumption and selling
decisions. . . . . . . . . . . 58

6 Income-quantity or farm size-quantity relation-
ships for the Guatemalan small farmer, given his
land constraint . . . . . . . . 63

7 Hypothetical production and distribution activities
for basic grains produced in the different regions
of Guatemala . . . . . .... . . . 71

8 Income-quantity relationships for the associations
by regions of Guatemala. . . . . . ... 103

9 Farm size-quantity relationships for the associa-
tions by regions of Guatemala . . . . .. 104

10 Price-quantity relationships for the associations
by regions of Guatemala. . . . . . ... 105

11 Income-quantity relationships for corn by regions
of Guatemala . . . . . . . . .. . ll

12 Farm size-quantity relationships for corn by
regions of Guatemala . . . . . . . 112

13 Price-quantity relationships for corn by regions
of Guatemala . . . . . . . . . 113

xiv








LIST OF FIGURES--continued


Figure Page


14 Income-quantity relationships for beans by regions
of Guatemala. . . . . . . . . . 117

15 Income-quantity relationships for rice by regions
of Guatemala. . . . . . . . . .. . 122

16 Farm size-quantity relationships for rice by
regions of Guatemala. . . . . . . ... 123

17 Farm size-quantity relationships for wheat by
regions of Guatemala. . . . . . . ... 127

18 Traditional and commercial income,farm size, and
price-quantity relationships in developing
agriculture . . . . . . . . .. . 151

A-I Mathematical properties of the specified function 171











Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy

TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE
IN AGRICULTURAL DEVELOPMENT:
THE CASE FOR BASIC GRAINS IN GUATEMALA

By

Jose Alvarez

June, 1977

Chairman: Chris 0. Andrew
Major Department: Food and Resource Economics

A growing population with about two-thirds employed in agriculture,

a limited arable land base, and poverty stricken farmers experiencing

unemployment and low levels of food production are characteristics

that portray Guatemala as a developing country The nation's develop-

ment efforts focus on the implementation of programs designed to alle-

viate those detrimental characteristics.

Program objectives at the Institute of Agricultural Science and

Technology (ICTA) of Guatemala intend to develop new technologies de-

signed to generate productivity increases especially for basic grains

in the traditional farm sector. These programs will enable the country

to augment supply without expanding the area committed to production.

Two types of problems, however, may result from productivity

advances. Small farmers could use the new technology to produce the









same or even a reduced quantity of grains on less land. Or, if land

is ful ly utilized, "second gencrat ion" marketing g problems are likely

to appear.

To a ioid cither type of problem, the investigation of traditional

and commercial supply response becomes of utmost irportarnce. Accordingly,

the objectives of this study were to estimate market supply functions for

each basic grain or association (combined crops such as beans-corn) in

the different regions of the country; to compute income, farm size, and

price elasticities of market supply; and to delineate and quantify the

corresponding production and distribution activities. A model con-

ceptualizing the small farmer's basic economic system was developed.

The surplu_-output raLio was estimated as a function of the product's

farmgate price education of household head, total farm size, distance

to the nearest market, quantity of the product demanded on the farm, a

relative profitability ratio, and total family income. Data used came

from a 1974 Small Farmer Credit Survey conducted by the Guatemalan

government and the U.S. Agency for International Development.

Research results, from the input standpoint, show that basic grain

production is most influenced by seed and fertilizer costs. While

fertilizer use tends to be a generalized practice, with the level of

application depending upon crops and regions, pesticides and soil

additives are not commonly utilized. All enterprises present different

levels of employment by region except for the associations where labor

use per hectare is very similar.


xvii








Total production differs among enterprises with respect to yields

and product distribution. Variations in cash sales are the result of

differences in farm demand for production and consumption purposes;

the more traditional the crop, the lower will be sales.

The results of the regression equations support the conceptual

model; in general, the estimated coefficients behave as hypothesized.

Traditional crops generally appear at near zero income and farm size

levels while commercial crops are cultivated when higher levels of

income and farm size have been attained. Elasticities of market

supply for traditional and commercial crops are high at low levels

of income and farm size. However, v.~hile commercial crops still show

some responsiveness at higher income and farm size levels, the tra-

ditional crop response becomes almost perfectly inelastic. This

behavior is the result of farmers becoming involved in the activities

of the market economy once self-sufficiency has been secured, and

shifting into commercial crop production at higher levels of income

and farm size.

Thus, since traditional crops pervade the basic grains production

system in Guatemalan agriculture, little hope prevails for the attain-

ment of massive increases in supply of basic grains. Although corn

in regions three and four and rice in regions four and five seem to

have a slight potential for increased production, the resulting in-

creases -would fall far behind the goal of the Guatemalan government.

xviii













CHAPTER I


INTRODUCTION


This chapter presents the problematic situation and the environment

within which this research project evolved. Some of the most important

agricultural and development related characteristics of Guatemala are

described, followed by the problem setting and the objectives of the

study. The importance of the project is discussed briefly. The data

source is explained, as are the important considerations concerning use

of the data in the present study.


Setting of the Study


Although a developing nation sharing certain characteristics with

other Third World countries, Guatemala possesses unique characteristics

to differentiate the country from other nations. To better understand

the present study, some of Guatemala's most important physical, demo-

graphic, economic, and social characteristics are described in this section.


Physical Environment


Guatemala, with an area of approximately 42,000 square miles (ex-

cluding British Honduras or Belize, which Guatemala claims as its




This section is based on [24].

1








territory), lies entirely within the tropics. It is bordered on the

north and west by Mexico, by the Pacific Ocean on the south, by El

Salvador on the southeast, on the east by Honduras and the Gulf of

Honduras, and on the northeast by British Honduras.

The climate ranges from hot and humid in parts of the lowlands

to very cold in the highlands. This wide range in climatic variation

permits the cultivation of any crop grown in the Western Hemisphere.

Landforms are also in great variety. The altitude varies from sea

level to over 13,000 feet in the volcanic highlands.

Rainfall occurs mostly from May to November and varies geograph-

ically. The Caribbean coastal plain and adjacent areas receive the

heaviest annual rainfall, which may reach 200 inches. On the Pacific

side annual rainfall is less and diminishes toward the coast. Guatemala

City, in the highlands, averages about 45 inches of rain per year.


Population


Guatemala is the most populous country in Central America--4.3

million inhabitants according to the 1964 Census. The Guatemalan pop-

ulation growth rate, one of the highest in the world, was approximately

3.1 percent per annum at the time of the 1964 Census. It is expected

that by 1980 the population of Guatemala will reach 7 million people.

Extremely high birth and death rates produce the consequent problems of

a young population with over half under 18 years of age.

The population is predominantly rural (66 percent of the population

according to the 1964 Census) and is concentrated in the highlands, where

the population density has greatly reduced the available land. In 1964,








the population density of the country, considered among the highest in

the Western Hemisphere, was 102 inhabitants per square mile.

In the 1950 and 1964 censuses the population was divided into two

groups: Indian and non-Indian or ladino. The first group encompasses

those of pure Maya Indian descent who continue to live much as their

ancestors lived several hundred years ago. The second group, in its

broadest context, comprises those neither belonging to an Indian com-

munity nor wearing the traditional Indian dress and following Indian

customs. Since ladino is a cultural term, it may be possible for some-

one who is accepted as a ladino in a rural environment to be classified

as an Indian in the urban milieu.

According to the 1950 Census nearly 72 percent of the population

over seven years of age was recorded as illiterate. This figure declined

to 63 percent in the 1964 Census, with almost 79 percent of the rural and

over 36 percent of the urban populations still illiterate.

Although Spanish is the official language and is spoken by a majority

of the population, over 40 percent of the population speaks a native

lanugage, with each township having its own dialect. Over 17 different

Indian languages and hundreds of township dialects create special prob-

lems for the total integration of the population within the mainstream

of national life.


Government and Political Subdivisions


Guatemala is a Republic with three branches of government: executive,

legislative, and judicial. The Republic is comprised of 22 major polit-

ical subdivisions (similar to states) called Departamentos (Figure 1),

each Departamento being divided into a number of municipios (similar to























D 0|*Lfl . a=**a*

-.-*l-00 ....**- .- -.
e....soa -e~








.. ..--


I. o.-..'n.. -.o es...
(ll, r (**i ui *r-Oi -




i, r I*'- / II --





;1 . l^ -- ~ ~
C-- I S >..






..,: iJ --j -. i.'-
r" cjjs o c*-,
/*II'CD e-l:-0 -1 -






/V" '' ''




t '" -


MEXIC 0


r -t "


BEULIZE
B iB '.sh Ho-irdur
1 i







r
, I






r^ '''^-- - -^
I ,-'



-r ' --


,- )- 0 '
-A .


u,ttij


- r



EL SaLV-00R i. / *.,


- 1 a1 8 '


'4,,ftrtA.I I
- - lh PCU'L'- y~ xli r
LflAJ qC.Lt


Figure 1.--Political divisions and transportation

routes of Guatemala


Source: [24, p. xiv].


0 *..'.. ,


10 1..





5


counties) of which there were 325 in 1964. The cabecera (capital of a

municipio is c31led either a pueblo (village), or a villa (larce village),

or a ciudad (city) if it is also a Department capital. The municipio is

made up of a number of aldeas (hamlets) and caserros (small rural commu-

nities) and the cabecera of the municipio is divided into cantones (wards).


The Economy


Guatemala's Gross National Product (GNP) is the largest of the

Central American countries, reaching 1.5 billion quetzales in 1967 (one

dollar is equal to one quetzal). Although growing at an average rate

of 5 percent annually since 1950, the economy's growth has been erratic

with substantial fluctuations in the annual growth rate of Gross National

Product. Per capital income has been growing at a rate of about 2.5 per-

cent since 1957; it changed from less than Q170 in 1955 to Q314 in 1966.

Traditional farmers' annual income is estimated at about Q85.

Guatemala's economy encompasses three major sectors: domestic food

production, export crops, and industry. Construction and miscellaneous

services supplement the three main sectors. The Indian economy, predom-

inantly subsistence agriculture, is largely self-supporting and regional.

The Indians are not completely integrated into the money economy and sur-

plus production, when present, is usually bartered or sold in local mar-

kets. Items for which the Indians can not barter are purchased with

money earned during the harvest season by working for wages on planta-

tions. Domestic crop production is characterized by its low level of

productivity as the result of primitive agricultural techniques and a

rigid land tenure system all of which sometimes require the importation

of food.








Much of commercial agriculture is managed by foreign firms, such

as fruit companies, the ladino aristocracy, and also by the Government.

The rapid development of export products such as coffee, cotton, sugar,

and beef contrasts with the stagnant characteristics of the domestic

food production sector, which has been unable to develop.

The industrial sector, although mainly concentrated in food pro-

cessing, is rapidly expanding, having grown at an average annual rate

of 10 percent between 1961 and 1967. This growth rate was stimulated

by laws designed to grant tax benefits and by participation in the

Central American Common Market.


Agriculture


Agriculture is the dominant sector of Guatemala's economy. The

agricultural sector has accounted for more than 80 percent of all ex-

ports since 1953; it provides about 30 percent of all raw materials

used by domestic industries; and the sector employs about two-thirds

of the population. Agriculture also accounts for about one-third of

GNP.

Major crops are corn, rice, wheat and beans and three major export

crops--coffee, cotton, and bananas. Minor export crops include essential

oils, tobacco, and honey. Crops primarily for domestic use include

rubber, cacao, fruits and vegetables, sorghum, millet, sesame, potatoes,

cassava, and hard fibers. Livestock and poultry are also important and

have grown rapidly in the last decade.

Agricultural activities take place within a very rigid system of

land tenure. Over 98 percent of the farms have an area under 100 acres








and occupy 28 percent of the land being farmed. On the other hand,

only 0.1 percent of the total number of farms are larger than 5,000

acres, but they occupy 41 percent of the farm land. In the 1950

Census, 1.3 million people lived on landholdings averaging 3.5 acres,

the minimum amount considered sufficient to satisfy the basic needs

of one family. In 1965, the situation was even worse; the Guatemalan

National Planning Council estimated that the number of landless fami-

lies had increased by 140,000 and that over 90 percent of all rural

families were either landless or possessed insufficient land for sub-

sistence.


Markets and Marketing


Markets and fairs occupy a very important place in the life of

rural Guatemala. Each community holds at least one special market

day per week, which is a socio-economic institution. Although these

markets are the traditional response to the economic conditions of

Indian life, pricing is determined not by customs but by supply and

demand conditions. Sellers are mainly Indian women; buyers are both

Indians and ladinos. Products, ranging from food to handicrafts

and clothing, are displayed by type and origin. Each township is

known for a particular commodity being less expensive than in other

markets. They may continue for several days and attract people from

all over the country.

Besides markets and fairs, marketing activities in the country-

side take place in small general or neighborhood stores. These stores

are often located in the onwer's home. In larger towns, stores are of

a permanent structure and owners are professional merchants.








Guatemala City, the capital, possesses a large number of retail

stores, one large plaza market for each of 15 zones, a central market,

and a number of well-stocked supermarkets. The capital is also the

principal marketing and distribution center for all imports.

Marketing activities are severely handicapped by the bad quality

or lack of communication. Certain regions of the country still remain

relatively isolated (Figure 1). Much of the produce for domestic

trade is carried to the local market on the backs of men and mules over

dirt trails and footpaths.


Foreign Trade


Guatemala's foreign trade is characterized by a large number of

trading partners, a short list of commodities traded and for most years

an unfavorable balance of trade. Guatemala maintains commercial rela-

tions with about 76 countries and is signatory to several international

agreements. The United States is Guatemala's primary, trading partner,

although this share has been slowly decreasing. Coffee, cotton, sugar,

beef, and bananas are the main exports. Nickel and flowers are new

promising export products. Consumption goods are the primary imports.

In each year between 1957 and 1969, with the exception of 1966, Guate-

mala experienced unfavorable trade balances which had to be financed by

credits and loans.

Agricultural products are the most important items of foreign trade.

Very low levels of grain production in Guatemala have forced the impor-

tation of cereals and the consequent annual deficit in cereal trade

(Table 1). From 1963 to 1972, agricultural imports represented 13.4 to





9


Table l.--Guatemala's imports and exports of cereals, 1963-72


Year

1963 1964 1965 1966 1967 1968 1969 1970 1971 1972
------------------Millions of U.S. Dollars----------------

Imports 7.6 8.0 7.8 7.0 8.6 8.7 7.0 10.2 9.9 10.8

Exports 0.1 0.2 0.6 0.8 1.0 1.1 1.2 1.8 1.3 2.5

Deficit 7.5 7.8 7.2 6.2 7.6 7.6 5.8 8.4 8.6 8.3

Source: [117, p. 84].








9.2 percent of total imports. Agricultural exports, on the other hand,

have represented between 69 and 88 percent of total exports during the

same time period (Table 2). For both imports and exports, agriculture's

share of trade had declined. Yet it is important to note the extremely

important role played by the agricultural sector's export surplus in the

overall trade balance situation for Guatemala. Over the 1963-72 period

this role increased as the share of agricultural imports of total agri-

cultural trade declined from about 14 percent to 11 percent.


Setting of the Problem


Introduction


The above description portrays Guatemala as a developing country.

Most of the characteristics described are common in other Third World

countries. First, the country's population, especially the rural pop-

ulation, is growing rapidly. The Guatemalan population growth rate at

approximately 3.1 percent per annum is high. When the population of

Guatemala reaches a projected seven million people in 1980, 63 percent

of the economically active population will be employed in the agricul-

tural sector. Compared with 65 percent in 1964, this represents an in-

significant decrease. Although employing 65 percent of the labor force,

agriculture only contributes about 30 percent to the Gross National

Product [35].

Another characteristic common to Third World countries is that

Guatemala has a limited arable land base. Yet a large percentage of

privately owned land is idle as a result of the prevailing land tenure








Table 2.--Guatemala's agricultural imports and exports, total imports
and exports, and agricultural percentage of total, 1963-72


IMPORTS EXPORTS

Year Agricultural Agricultural
agriculturee Total percent Agriculture Total percent
of total of total
----------------------Millions of U.S. Dollars---------------------

1963 22.9 171.1 13.4 135.2 154.0 87.8
1964 24.0 202.1 11.9 140.1 166.8 84.0
1965 25.2 229.0 11.0 156.6 185.8 84.3
1966 24.4 206.9 11.8 185.4 226.1 82.0
1967 30.1 247.3 12.2 140.6 203.9 69.0
1968 29.1 249.4 11.7 164.4 222.2 74.0
1969 24.3 250.2 9.7 186.3 255.4 72.9
1970 31.5 284.3 11.1 200.9 290.2 69.2
1971 31.3 303.3 10.3 198.5 283.1 70.1
1972 30.0 327.7 9.2 234.8 328.1 71.6

Source: [117, pp. 52-9].








system 124, p. 260]. Nearly all arable land in the highlands is pre-

sently under production. Government policies prohibiting tree removal

to bring new land into production in regions such as El Peten contri-

bute to a land scarcity condition that is further aggravated by the

population situation.

A third characteristic, common to other Third World countries, is

that many Guatemalan farmers live in poverty conditions, are often un-

employed and unemployable, and have very low levels of food production.

For example, net income per capital in the central highland region has

been estimated recently to be Q117 per annum [26, p. 431. In the same

area, real product per capital went from Q77 in 1951 to Q51 in 1966 135,

p. 23]. A recent study conducted by the Institute of Agricultural

Science and Technology (ICTA) in the community of Santo Domingo Xenacoj

supports these figures [17]. The community, where family income averages

from Q90 to Q200 per year, is plagued by such a high unemployment rate

that part of its population is forced to migrate to cities and the

coast in search of new employment opportunities.

Successful efforts directed to solving population, employment, land

use, and income problems will benefit Guatemalan development. The imple-

mentation of programs leading to more intensive land use, the reduction

of unemployment, and the increase in production and productivity in rural

areas ought to receive top priority among the country's development

efforts.

Agriculture, especially small farm agriculture, can play an important

role in Guatemala's march towards economic and social development. In

1951 a mission sponsored by the International Bank for Reconstruction and








Development reported that "it is clear that any appreciable rise in

Guatemala's standard of living can come only through improvements in

agriculture" [51, p. 27]. Several researchers have suggested that

programs to improve agriculture should be oriented toward small rather

than large farmers because small farmers utilize scarce resources more

efficiently in food production [19, 35, 47]. Furthermore, the contri-

bution of the traditional small farmer to overall production, especially

basic grains production, is relatively large. Fifty-five percent of

total basic grains production in the country comes from farms under

seven hectares. Waugh states that it is evident that the small farmer's

production is of first order of importance to the country. He goes on

to say that this production results from a very limited percentage of

the land in farms and that 67 percent of the total number of farms in

the size group 1.7 to 7 hectares have only 18 percent of the total land

in farms [118, p. 2]. Furthermore, it is in the small farm sector where

economic and social development are most needed.

Certain characteristics of Guatemalan agriculture necessitate pro-

gram formulation at the subsector level. Fletcher et a11[35, pp. 51, 53]

identified three subsectors in Guatemalan agriculture: the traditional

agriculture of the highlands (corn, beans, wheat) and other parts of the

country; export crops (coffee, cotton, and bananas); and commercial agri-

culture mainly for domestic consumption (the majority of the remaining

crops). Since these subsectors face different produce demand schedules

and marketing problems, agricultural development programs will be most

successful when formulated at the subsectoral level. Accurate problem

identification leading to specific solutions for each subsector would








then be easier. This study is mainly concerned with the traditional

(subsistence) and commercial subsectors of Guatemalan agriculture. A

distinction ought to be made between traditional and commercial Farmers,
2
and between traditional and commercial crops. The term traditional

farmer does not necessarily include only Indian pre-Colomhian types of

agriculture; it is also used to signal farmers who historically ignore

market stimuli and are not prepared to shift from one crop to another;

they can not respond easily (neither economically, culturally, nor

technologically) to stimuli. In general, the term traditional means

any system which has been used for "a long time" and has not been

"modernized" particularly in the use of petroleum based products. Al-

though these farmers may use some fertilizer in some regions (where

water is available), they apply almost no insecticides (ownership of a

sprayer means an additional investment). The commercial farmer is

price responsive and has the means to shift between crops; his farming

is a business and he responds to market stimuli.

The difference between traditional and commercial crops is based

on the destination of the product and the utilization of labor in its

production. In traditional crops, farmers tend to use about 80 percent

family labor and 20 percent contract or hired labor, and, although some

output may be sold when a surplus occurs, production is mainly devoted

to family consumption. In commercial crops the characteristics are




The discussion is based on personal communication with Peter E.
Hildebrand, Coordinator, Socioeconomics Program, ICTA-Guatemala.








almost exactly the reverse. These sharp distinctions among subsectors

validate the assertion concerning the necessity of formulating programs

at the subsectoral level.

Work at the Institute of Agricultural Science and Technology (ICTA)

of Guatemala is focused on subsectoral problems. On January 20, 1976,

the Minister of Agriculture of Guatemala announced that the government

was launching a program to increase agricultural production with special

emphasis on basic grains [22, p. 1]. Accordingly, ICTA's 1976 plan com-

prises production programs for different agricultural products (corn,

beans, rice, wheat, sorghum, vegetables, and hogs) with the support of

disciplines such as Soil Management and Rural Socioeconomics. The crea-

tion of the Program of Rural Socioeconomics is the result of ICTA's

policy based

... in the belief that an appropriate technology can only
be developed through the study of the causes conditioning
the application of new technologies and this is achieved
by means of agro-socioeconomic studies at the farm level
in continuous contact with the farmer who will be its
principal usufructuary. Therefore, the contribution of
the social sciences (Economics, Sociology, Anthropology),
is the key which will enable us to know these causes and
will permit the recommendations to be based on the agro-
nomic research and correspond to the requirements of the
environment to which they are intended...[53, p. 2171.


Problem Statement


ICTA's subsectoral programs are intended to develop a new tech-

nology based on the environment in which farmers live, to generate

productivity increase that make it possible for Guatemala to supply

its growing population with more agricultural products per capital

without an increase in the area used in production. For example,








several diseases and weeds affecting corn have been controlled and,

by utilizing a new seed variety, yield per acre in La fiaquina, located

in the Suchitepequez Department, can be doubled and even trebled.

Another example pertains to research on interplanting beans with corn

and on insecticides and new seed varieties that will eventually lead

to larger bean yields. Research on wheat is seeking new seed vari-

ties with high productivity and resistance to primary diseases and

adapted to different regions of the country and small farmer use.

The new wheat variety, "Gloria", introduced in the Cooperative Santa

Lucira, R.L., hEs' doubled wheat production and has been accepted by

the farmers of the area [52]. Since the new technology is being de-

veloped considering the conditions and limitations that farmers face,

farmers are making full and best use of the technology.

The adoption of the new technology, it is hoped, will foment

increases in production and productivity. In Guatemala, as in most

developing countries, a large portion of agricultural production is

consumed on the farm. Thus, the adoption of new production techniques

may arise from the desire to sell the extra production for cash. Very

little is known, however, about the intensity of marketing and consump-

tion problems that must be faced if farmers market most of the increase

in output.

An increase in marketed output may intensify the strong tendency

towards price instability inherent in the marketing of agricultural

products. Abbott attributes instability to the seasonal concentration

of output, great difficulties in adjusting production closely to demand









in view of the uncertainties of weather and yields, and to the rela-

tively low price elasticities of demand for the basic food products

[2, p. 6].

Productivity advances can also show how rapidly the so called

"second generation marketing problems" can arise. Falcon, when

writing about the Green Revolution, expressed his hope that decision

makers in the future will heed the warnings earlier of marketing spe-

cialists and will react before critical product distribution situa-

tions develop [32]. Such problems range from the early identifiable

problems related to drying, storing, transportation, etc., to the

less identifiable, but not less important, problems of pricing and

markets. It is extremely important to face these problems on a

timely basis, avoiding the erroneous belief that marketing is an

accommodating, spontaneously generated activity that can be somehow

performed once production has been increased. The following research

is addressed to more fully understanding the differences in supply

response in the traditional and commercial subsectors due to changes

in agricultural technology.

Market problems in the future will combine with those at present

such as unstable agricultural prices, the absence of adequate marketing

channels for both inputs and outputs, and the lack of knowledge concern-

ing demand and supply relationships. The vast importance of corn to the

national economy and, in particular, to small farmers in the highlands

has been documented [98], yet it is surprising how little information

related to corn marketing is available. For example, there are no com-

plete and reliable data for corn moving through the different marketing








channels. The lack of drying and storing facilities causes concern to

government oFFicials, wholesalers, and farmers. Surveys conducted by

the Agricultural Marketing Board reveal substantial differences in

losses during marketing among the different zones of production due

to differences in storage, transportation and processing. Fletcher, et al.

say that the majority of the important problems prevailing in corn

marketing are related to the lack of adequate facilities for drying

and storing [35, p. 43], which causes substantial losses and produces

considerable variation in the price of corn (Figure 2 and Table 3 to

Table 5). The variability in the price of corn may benefit those who

can store large amounts of corn for three to six months, but neither

helps the small farmer who needs cash at the time of harvest nor the

consumer who buys this product in small quantities. The same phe-

nomenon prevails in bean marketing (Figure 3 and Table 3 to Table 5).

Price stabilization for corn and beans, therefore, is an important

objective of the Guatemalan government.

The need for conducting supply and demand studies in the rural

areas is evident. An important aspect on the demand side is the quan-

tity of basic grains that small farmers demand. Since much of their

production is consumed on the farm, knowledge of their demand is needed

to estimate the future amounts of basic grains they will send to the

market as a result of increased production. Since the nature of the

available data does not permit the identification of demand functions,

this research will be focused mainly on supply.







19




cu








< CN











o
6 ci









-



I C













0-
I U






















/. ."%
r-
I m u





































L U
C'4
























0 L 0 C 0 .L

o u nZ jad s ezian b
-e




('1-3







L


a)













L LI\


-CN

L u

cn



CO L C i.' L. C Lr. 0 LI. O LI



IClu!fn .id salez1an?








Table 3.--Average wholesale prices for beans and corn, in Guatemala
City, 1972


Black White Red Yellow White
Month
Bean Bean Bean Corn Corn
------------------Quetzales per Quintal-----------------

January 7.77 10.08 7.47 2.90 2.73
February ---- ---- ----
March 7.85 10.14 7.65 2.82 2.64
April 7.50 9.96 7.58 2.74 2.89
flay ---- ----
June ---- ---- ---- ---- ----
July 7.18 11.00 7.58 2.80 2.90
August 9.12 12.01 9.06 3.22 3.22
September 9.10 12.44 9.92 3.22 3.33
October 9.16 12.14 10.30 3.42 3.07
November 10.75 12.69 11.31 3.83 3.77
December 13.35 11.86 14.98 4.95 4.95


Source: [55, 56].








Table 4.--Average wholesale prices for beans and corn, in Guatemala
City, 1973


Black White Red Yellow White
Month
Bean Bean Bean Corn Corn
------------------Quetzales per Quintal-----------------

January 11.15 13.08 11.73 4.79 4.80
February 12.08 13.53 12.73 4.91 4.94
March 13.75 14.23 13.48 5.14 6.07
April 12.47 14.56 13.46 6.50 7.23
May 12.35 14.67 13.73 6.42 7.02
June 14.85 17.84 15.88 6.07 6.61
July 14.33 19.35 16.80 5.87 6.46
August 10.60 15.93 11.97 5.29 5.62
September 12.36 15.00 12.99 4.92 5.18
October 15.48 15.19 14.05 5.59 5.25
November 18.24 15.03 14.63 6.55 6.16
December 17.08 15.20 15.34 6.46 6.08

Source: [551








Table 5.--Average wholesale prices for beans and corn, in Guatemala
City, 1974


Black White Red Yellow White
Month
Bean Bean Bean Corn Corn
--------------------Quetzales per Quintal----------------

January 16.39 14.90 15.35 6.22 5.98
February 16.13 15.00 15.38 6.13 6.01
March 16.61 16.44 16.83 6.90 7.07
April 15.53 15.58 15.91 7.77 7.97
May 16.09 15.90 16.80 7.03 7.09
June 16.86 16.72 17.53 6.70 6.60
July 17.88 17.79 18.44 6.72 6.56
August 14.87 15.54 14.76 6.46 6.25
September 15.21 15.33 15.03 6.62 6.51
October 17.77 16.06 16.03 6.48 6.30
November 19.78 18.02 17.82 6.65 6.44
December 19.04 18.33 18.33 6.88 6.78


Source: [55]



























N.


T- \



*" =:;; **. .


1 I I I I


o Ca\ cO r L -- r N O 0


iP1U!inl jad sa[ez3ano


rI


E








C
(D




















o-,
c





(U
-o


C

















0 '
r_











U
r4








LO











0 1


CD





L >*-
cii


















IL


c0 r*-


I


I I I I


:~ '"

I,


- --


I I I I


" -"








On the supply side, detailed market knowledge and research on

where, when and for what price products can be sold is essential in

determining what to produce. Due to very large seasonal and cyclic

fluctuations in the prices of agricultural products, farmers in de-

veloping countries rationally choose to grow sufficient food for

home consumption. Market supply functions are important in deter-

mining how responsive farmers are to price, income and other variables

for policy decisions aimed at securing adequate increases in the mar-

keted supply of food crops. Since the responsiveness will be different

in different milieus, elasticities of supply must be estimated separately

for different regions. Market supply functions may also signal possible

future changes in land utilization. It has been observed very recently

in the communities of San Martin Jilotepeque and El Novillero that, as

the small farmer obtains a better standard of living resulting from

new corn technologies, there is a tendency to reduce the amount of

land devoted to corn production since this is mainly cultivated for

family consumption [107].

Knowledge of the characteristics of production and distribution

activities is needed. Their description and quantification, especially

in the market for inputs, will show cost and availability of inputs in

each region. Comparing results with actual output in the region may

provide a basis for identification of problems that can be solved by

policy decisions. In a marketing study of basic grains, the Institute

of Agricultural Marketing (IrIDECA) delineated the marketing channels

for these products [54]. The study lacks, however, the corresponding








data for each channel and therefore it is impossible to know the relative

importance of each channel; it also contains no information about the

movement of inputs to small farmers.

There is no doubt that the existing problems and those that will be

generated by the increase in production and productivity of basic grains

require careful study to avoid the imminent "Green Revolution" second

generation problems. Knowledge of total supply and marketed supply

functions, production and distribution activities, and the behavior of

the surplus-output ratio as income and farm size change, is important

in solving present problems and in trying to avoid major market problems

in the future. It is in this context that the following objectives are

undertaken.


Objectives of the Study


The objectives of the study are to:

1. Estimate market supply functions for basic grains in the

different regions of the country and compute the corresponding

income, farm size, and price elasticities of market supply.

2. Delineate and quantify input acquisition and product dis-

position for basic grains in the different regions of the

country.


Data Source and Data Considerations


The data are derived from the Small Farmer Credit Survey conducted

by the Government of Guatemala and the Agency for International Develop-

ment (AID) in 1974 for agricultural activities during the 1973 calendar








year. These cross section survey data contain necessary and valuable

information for conducting this research since time series data are

completely unavailable. The overall objective of the survey was to

compare the performance of small farmers receiving credit from the

government with non-recipients. A sample was selected by sub-region

in order to have a minimum number of sample farms producing the desig-

nated main crop for each sub-region. Interviews were taken with 800

pairs of farms, from which a total of 1,548 questionnaires were com-

pleted. Figure 4 shows the different regions with their respective

important crops. Table 6 and Table 7 present the number of sampled

farms and farm size by region, sub-region and department, respectively.

By reviewing Figure I, it becomes evident that the survey reached every

Department in the nation, except El Peten (Region two) which is a semi-

isolated area in the process of colonization.

A word of caution about the representativeness of the data is appro-

priate. The no-credit farmers were selected because of their similarity

in age, size of farm, crops grown, etc., to the group of farmers receiving

credit. Therefore, the former group would represent all farms in

Guatemala only to the extent that the latter group does. Interest how-

ever falls in drawing conclusions about traditional and commercial agri-

culture at the regional level. In this case the sample does contain

enough farms engaged in either or both types of agriculture such that

conclusions by farm type at the regional and national levels are possible.




Complete descriptions of the sampling procedures are available in
[19, 106]. More information about the survey's results is contained in
[75, 92, 101].

































Central Highlands


wheat
corn
milpa
potatoes


Peten
(not included in sample)


Northeast

corn
beans
milpa
potatoes
rice
tomatoes
onions


corn
)m beans
same rice
lme
ce sorghum
coffee South Coast
plantain
sesame

L...,


Figure 4.--Important crops in the different regions of Guatemala


Source: [19, p. 14]


Southeast
Highlands


;** *



-r.








Table 6.--Nlumber of sampled farms by region and farm size


Farm Size
Region
0-0.9 1-2.9 3-4.9 5-9.9 10+
All Sizes
Ha. Ha. Ha. Ha. Ha.

I Central Highlands 64 145 75 56 40 380

3 South Coast 5 10 14 14 59 102
(West)

4 South Coast 7 68 49 75 89 288
(East)

5 Northeast 28 151 86 83 134 482

6 Southeast
Highlands 9 77 75 59 76 296

National Totals 113 451 299 287 398 1548

Source: Computed from [19, p. 20]








Table 7.--Number of sampled farms by region, sub-region,and department


Region Sub-Region Department No. Department Name No. of Observations

1 1 13 Huehuetenango 96
2 12 San Marcos 48
2 9 Quezaltenango 52
3 9 Quezaltenango I
3 14 Quiche 40
3 8 Tontonicapan 23
3 7 Solala 30
4 4 Chimaltenango 54
4 3 Sacatepequez 36
380
3 5 12 San Marcos 32
5 II Retalhuleu 49
5 10 Suchitepequez 21
102
4 6 5 Escuintla 50
7 5 Escuintla 91
6 10 Suchitepequez 45
6 3 Sacatepequez 1
7 4 Chimaltenango 1
8 6 Santa Rosa 84
8 21 Jalapa 5
8 22 Jutiapa II
288
5 9 16 Alta Vera Paz 89
9 6 Santa Rosa 1
9 15 Baja Vera Paz 4
10 15 Baja Vera Paz 78
10 14 Quiche' 16
10 10 Suchitepequez 4
11 19 Zacapa 81
11 2 El Progreso 19
12 2 El Progreso 30
12 1 Guatemala 64
13 18 Izabal 96
482
6 14 22 Jutiapa 98
15 21 Jalapa 77
15 6 Santa Rosa 19
16 20 Chiquimula 102
296
Total 1548

Source: [19].








George and King's arguments in support of the use of cross-section

data in their research [371 can be extended to the present study. First,

time-series data are not available; but even if they were, more reliable

(demand) parameters can be estimated with cross-section data. In static

analysis, a (demand) relationship is specified for a particular period

of time. In practice, as George and King point out, [37, PP. 28-91 each

time an observation is made, we get one point on a (demand) curve and,

by the time another observation is made, the curve might have shifted

because one or more factors influencing (demand) may have changed.

These shifts may influence the nature of functions obtained from time-

series analysis and, at times, it will be difficult to isolate the

effects of such shift variables from purely economic variables such as

prices and income. Thus, wrong conclusions about the non-significance

of economic variables in explaining (demand) could be drawn.

Second, since prices generally remain unchanged during a short

period of time, cross-section data make it possible to estimate income

elasticities free from price effects. George and King state that cross-

section data primarily reflect the (demand) pattern in the sense of

long-run income changes so that the income elasticities computed from

these data can be interpreted as long-run elasticities. From the point

of view of practical applications of (demand) analysis, these long-term

elasticities are more relevant for many policy decisions than the short-

term elasticities obtained from time-series data.









Relevance of the Project


Income and farm size elasticities of market supply are important

determinants in signaling farmer behavior concerning potential increases

in quantities produced and marketed and in land utilization. These elas-

ticities permit the estimation of the effects that may result from future

increases in productivity and production, if in fact they occur, and in

income. Price elasticity may also be computed but would be less mean-

ingful due to the nature of the data. Price observations from the cross-

section data available do not capture seasonal prices because interviews

were taken at one time due to research resource constraints. The aggre-

gate prices taken can create price elasticity situations without easy

interpretation and application. This drawback, however, appears to be

less relevant as emphasis is given to the income and farm size elastici-

ties and the income-quantity and farm size-quantity relationships as

indicators of farmer supply responsiveness to factors that change his

income and farm size.

One of the most important implications of testing the theory pre-

sented in this study is obtaining a better understanding of the basic

economic system of small farmers and the relationships between this

system and Green Revolution agriculture. The theory suggests that there

is a built-in supply control mechanism for basic grains and low value-

low risk crops in the small farm system. This mechanism, explaining why

productivity increases yet production is stagnant, is a natural reaction

to basic subsistence needs and avoids some of the second and third gen-

eration problems of the Green Revolution [32]. Overproduction may not








usually result so prices would not decline sharply to create great income

disparities and the usually disoriented market system itself would not be

so forcefully challenged.

Should these hypotheses prove reasonably accurate, research and de-

velopment programs might carefully consider the total small farm system.

Basic research on basic grains alone will not serve the small farmer's de-

veloping needs entirely as he moves into higher value-higher risk crops.

Meeting the risk element squarely in both agronomic and economic research

programs might be most productive.


Organization of the Dissertation


The setting of the study, with its problematic situation and impli-

cations, has been presented in this chapter. The theoretical framework

of the second chapter describes the role of agriculture and of marketing

in economic development, with special emphasis on the theory of demand

and supply in LDCs. After the theory and literature are reviewed, the

methodology used in accomplishing the objectives is presented in the

third chapter. The fourth chapter describes input acquisition and pro-

duct disposition for basic grains in the different regions. Chapter five

encompasses both the results and the corresponding analysis, and the

sixth chapter contains a summary, the conclusions, and recommendations

based on the results obtained. The final chapter, "Reflections on the

Theory of Development," is an attempt at actualizing the current develop-

ment literature of the second chapter in light of the findings in chapter

five.














CHAPTER II


AN EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT


That part of the development literature related to agricultural

development and marketing is summarized in this chapter. The rela-

tionships between agriculture and economic development are the subject

matter of the first section. The second section describes marketing

activities and their role in the development process with special

emphasis on the theory of demand and supply in developing countries.


Agriculture and Economic Development


Since World War II the literature has paid increasing attention

to the process of economic development in the developing countries.

There seems to be a consensus on the need for sustained growth to

bridge the gap that separates LDCs from the industrialized nations.

Though the problem of an overall development strategy is continually

discussed, the key role that the agricultural sector has to play is

today widely accepted. In this chapter, some of the most important

viewpoints, especially those related to the problematic situation

described above, are analyzed.








Agriculture in LDCs: A Changing Spectrum of Priorities


Arthur Gaitskell [36, pp. 46-50] has tried to explain why agricul-

ture until recently has experienced a very low priority in developing

countries. He enumerates the following reasons:

(a) Since the richest countries in the world are the industrial

countries, it seemed logical that industry, rather than

agriculture, was the means for development.

(b) Developing countries have been sources of raw materials

for the industrialized nations and a market for their

manufactured products, but their terms of trade have

been deteriorating. Developing their own industries,

therefore, seemed to be a correct goal.

(c) Private foreign investment was, for a long time, the

pattern of development without any national participation.

(d) Traditional values ("not everybody gives development top

priority in their lives"): Leisure, status, religious

precepts, traditional methods of ancestors, etc., played

an important role in hampering agricultural development.

(e) Decision makers in LDCs come from the educated-elite and

they are fundamentally urban oriented.

(f) Other reasons favoring industrialization were: it has a

greater appeal than agriculture to LDCs since it suggests

the modern world. Machinery can be imported; it is easy

to learn how to use it and see the results. Agriculture

on the other hand is old and most people think they

already know all about it. Industrial output is less








uncertain than crops. Since a minority is engaged in

agriculture in the industrial countries, industry seemed

the obvious target for which to aim. Finally, since in

the most developed countries, industry's surpluses have

been used to pay for subsidies, a cause for technological

success, the idea of developing industry first found

greater appeal.

There has been, however, a recent shift to complementary growth of

agriculture and industry. Gaitskell [36, pp. 50-6] attributes the atten-

tion given to agriculture to several facts:

(a) The existence of undernourishment and poverty is today a

main purpose for encouraging development. Since the main

areas affected are the rural areas, it follows that agri-

culture has to be developed.

(b) The "left-outs" from rural areas constitute a serious

threat to existing political regimes.

(c) Industrialization alone can not solve the unemployment

problem since it is capital intensive.

(d) Foreign exchange earnings from agriculture are necessary

to buy the basic imports needed for industrialization.

(e) The increasing need for food as population increases

and land becomes even more scarce.

The time has come for proper priority to be given to progress of the

agricultural sector in developing countries where resources are favorable

and population growth is pressing.








Agriculture versus Industry: A False Issue


The issue of establishing development priorities in LDCs is of

utmost importance. In the process of making a choice, economists

have embraced one of two opposing views: those recognizing that top

priority should be given to increase food supply, and those advocating

a "big push" industrialization program. Among the advocates for the

first group are A.E. Kahn, J. Viner, Coale and Hoover, and others,

while A.Hirschman, Liebenstein and Higgins, among others, belong in

the second group. Heady [46, pp. 66-7], though recognizing that there

is no universal rule for making a choice between the two, outlines

several cases in which a choice can be appropriately made in either

direction according to specific circumstances. Nicholls [89, p. 16]

believes that the choice is a matter of degree and not of kind, and

states that there is probably no developing country in which it is

feasible to concentrate all of its investment on either agriculture

or industrial development, and it will be impossible to concentrate on

industry until a reliable food surplus has been achieved and sustained.

Since in most LDCs there is still a large agricultural majority coupled

with large rates of population increase, Dovring [27, p. 95] wonders

how large the rate of industrizalization must be to absorb the annual

increments in the labor force and reduce the existing surplus in agri-

culture.

Meier's comments on the issue seem to summarize very well the

current status of the debate:

The attainment of a proper balance between the establish-
ment of industries and the expansion of agriculture is a per-
sistently troublesome problem for developing nations. In









earlier discussions of development priorities, deliberate
and rapid industrialization was often advocated. Experience,
however, has shown the limitations of an overemphasis on
industrialization, and it is increasingly recognized that
agricultural progress is a strategic element in the develop-
ment process. Industrial development versus agriculture has
become a false issue, and the concern now is rather with the
interrelationships between industry and agriculture and the
contribution that each can make to the other. It has also
become apparent that the relative emphasis to be given to in-
dustry and agriculture must vary according to the country
and its phase of development [80, p. 285].


The Role of Agriculture in Economic Development


Papanek [93, pp. 289-91] advances several economic arguments for

heavy emphasis on development of the agricultural sector. The arguments

apply to the commercial and large scale (capital intensive) farms. First,

it is necessary to free labor for industrial development. Second, agri-

cultural production can be raised rapidly and with little capital (pos-

sibility of doubling crop production, or raising crops in previously

uncultivated areas, fertilizer use, improved seeds, etc.), while indus-

trialization requires time and capital, skilled workers, managers, social

overhead capital and the like. Third, while the development of the

agricultural sector is capital-saving in requiring minimum expenditures

for overhead costs by obviating massive population movements, industria-

lization would require heavy expenditures to provide at least minimal

facilities to the new city inhabitants. Fourth, development of agri-

cultural production also is often the fastest method for decreasing needed

imports or increasing saleable exports in countries needing and lacking

foreign resources. Fifth, structural changes may be needed before

technical improvements in agriculture can be carried out without prior








industrialization. Finally, increased incomes will produce increased

demand for food and clothing. Agricultural production or imports will

have to be increased as part of the development process since reinvest-

ment of all of the increased production can not be expected.

The five propositions stated by Johnston and Mellor [58, pp. 291-

7] about the ways in which agricultural development, especially large

scale agriculture, contributes to over-all economic development follow

directly from the former arguments. First, economic development is

characterized by a substantial increase in the demand for agricultural

products, and failure to increase food production in pace with the

increase in demand can seriously impede over-all economic development.

Second, agricultural exports may provide foreign exchange earnings.

Third, the labor force for the expansion of the industrial sector can

contribute the capital required for overhead investment and expansion

of secondary industry. And, finally, rising net cash incomes of the

rural population may be important as a stimulus to industrial expansion.

There is no longer any doubt, according to Schultz [108, p. 51]

whether agriculture can provide a tremendous stimulus for over-all

economic development. It is only necessary to invest in agriculture

and, above all, to provide farmers with incentives. Once there are

investment opportunities and efficient incentives, as he puts it,,

farmers will turn sand into gold.

The role of agriculture in economic development according to

Nicholls [89, pp. 11-31 depends heavily upon the particular historical

circumstances of the country and upon the ratio of agricultural land

to population. The relative emphasis which decision makers give to









agriculture, and the consequent policies must therefore vary accordingly.

But it is clear for him that, either for an open or closed economy, the

agricultural sector can make tremendous contributions to over-all eco-

nomic development and that, within considerable limits at least, the

development of this sector is a sine qua non before a take-off into

self-sustained economic growth can become a reality.

In many countries, however, agriculture has failed to respond for

what Heady [46, pp. 63-4] calls obvious reasons. First, agriculture

has not been given an appropriate priority. Second, there is a lack

ofa price structure conducive to the use of new and more capital re-

sources such as insecticides, fertilizers, and improved seed varieties.

Third, input prices have been kept too high and output prices have been

kept too low. Fourth, capital has not been moved into the hands of

subsistence farmers to incorporate them into the market economy. Fifth,

frequently, the absolute supply of and the facilities to move and store

inputs are lacking. To eliminate those adverse factors, several eco-

nomists have suggested different prescriptions.


Some Prescriptions for Agricultural Development


Many sophisticated models have been provided for developing the

agricultural sector in LDCs. Except for Heady and Lewis, all of the

authors call for increasing employment on farms rather than replacing

labor with mechanized technology.

For Heady [46, p. 61] there is no mystery in the process of ex-

plaining the development of agriculture. It is so simple that no new

theory is required. He proposes the following "recipe":








Lower prices and increase availability of resources,
add certainty and greater quantity to product prices, blend
with knowledge and a firm or tenure structure which relates
input productivities appropriately with resource/product
price ratios. This mixture can be brought to a develop-
mental boil in a container of commercial farming, if not
successfully in a purely subsistence environment which is
outside the market economy. It will have a delayed or
lagged maturity, depending upon the dosage of the above
variables and the extent to which a very few specific
cultural factors exist. These factors include (1) creating
a new "state of mind" for cultivators who have previously
been oriented to production best guaranteeing food for
subsistence in the year ahead, and who must now look to
expansion towards the market, and (2) acquainting families
with the mysteries of managing credit and capital in order
to convert them from subsistence operations.

This recipe has been tested and proven successful over
many parts of the world: so much that it is doubtful that
anyone will ever come up with a better one. Hence, the
creation of the conditions implied above is one of the
priorities for bringing economic development to agri-
culture. There is no mystery to the process. If a
mystery exists, it is to explain those exogenous condi-
tions which prevent governments and planning agencies, which
wish agricultural development, from manipulating the above
instruments and going forward with the recipe [46, p. 63].


Lewis' well-known article on "Economic Development with Unlimited

Supplies of Labour" [74] deserves special consideration. According to

him, in most developing countries the supply of labor is perfectly

elastic at current wage rates. The existence of disguised unemployment

in the agricultural sector, with zero or even negative marginal pro-

ductivity, provides the basis for economic development. As workers

are absorbed by the industrial sector, capitalists earn a surplus, the

surplus can be invested with the resulting increase in marginal produc-

tivity and, therefore, growth. Despite the controversy that followed

publication of this position, the article exerted tremendous influence


in the 1950's and 1960's.









Premature displacement of labor from agriculture, however, could

hamper economic development. The demand for food (determined largely

by population growth and by the income elasticity of demand for food)

and the existing high rates of population growth with the difficulty

experienced by the urban sector to absorb this growth, yields the

Johnston and Mellor policy prescription of

...a labor-intensive approach with reliance on yield-in-
creasing technical innovations in the earlier phases of agri-
cultural development. This policy approach produces the
required increases in agricultural production and avoids
displacing labor prematurely from agriculture. It is a pre-
scription for agricultural research, for large increases in
the use of yield-increasing inputs such as fertilizer, im-
proved seeds, insecticides and pesticides, for increases
in irrigation facilities and for building service institu-
tions in extension, marketing, and credit. It is also a
prescription to minimize mechanization, especially when it
serves to displace labor [26, p. 45].

Dorner [25, pp. 268-72] also points out important areas in which

policy changes could strengthen economic development and the status

of the small farm subsector. Of special interest to our case are:

First, development and introduction of new technology to increase

employment and production, with special emphasis on land saving tech-

nologies if both increased production and employment objectives are

to be served. Second, modification of rural service structure to

assure access by small farmers.

No matter the prescription followed, it is essential to remember,

as Hirschman states, that "... development depends not so much on

finding optimal combinations for given resources and factors of pro-

duction as on calling forth and enlisting for development purposes

resources and abilities that are hidden, scattered, or badly utilized"








[48, p. 5]. And that "there are always and everywhere potential sur-

pluses available. What counts is the institutional means for bringing

them to life...for calling forth the special effort, setting aside the

extra amount, devising the surplus" [95, P. 339].


Marketing and Economic Development


A negative feature of pricing systems in developing countries is

the existenceof extremely high prices at the retail level restricting

consumption along with extremely low prices at the producers' level

which do not stimulate farmers to grow and market more products. There

exists no doubt that inefficiency in the marketing of agricultural pro-

ducts is characteristic of most developing countries. Despite the im-

portance of well organized and efficient distribution systems, the

study of the role of marketing in LDCs began only two decades ago.

The purpose of this section is to profile the important role that mar-

keting plays in economic development.


Marketing Defined


Marketing may be defined in several ways. In a broad sense, mar-

keting can be identified as "part of the production process that assures

market outlets for farm products and makes readily available supplies of

production inputs which reduce price uncertainty and risk" [115, p. 1].



IAbbott [2, p. 364] affirms that the first to point out specifi-
cally the importance of marketing in economic development was R.H.
Holton in the beginning of the 1950's.









In a conference about marketing problems in LDCs [66, p. 6], agri-

cultural marketing is considered to consist of four specialized areas

or activities. The first area, "factor marketing", encompasses the

functions of providing inputs for farming. The second is the movement

of commodities to consumers. The third area is concerned with the acti-

vities performed by the processor converting the commodities into pro-

ducts. The fourth is related to the export of the commodity.

Marketing operates in a certain environment and is affected by

different forces. Technology is, in our case, the most important factor

to consider. "Technology puts pressure on a marketing system to which

it must adjust, and similarly, technology has much to do with the pro-

ducts distributed and their eventual acceptance" [49, p. 2]. Reynolds

[100, p. 154] says that marketing is affected by technological change

in three ways: by change in goods and production methods, by changes

in the ultimate consumer, and by changes in marketing itself.


The Role of Marketing in the Economy


An AID publication [67,pp. 27-8] lists three broad functions that

the marketing system performs in the economy. First, it performs the

reciprocal function of providing an outlet for producers and commodities

for consumers (household and processing firms). Second, it provides a

livelihood for those performing the different marketing activities, and

should yield reasonable returns to the capital and managerial abilities

devoted therein. Third, it signals those engaged in the production,

distribution, and consumption of commodities the actions they should

take in their own interest.








The importance of marketing can be appreciated in the triple

functions enumerated by Drucker [28, p. 335]: the function of cry-

stallizing and directing demand for maximum productive effectiveness

and efficiency; the function of guiding production purposefully toward

maximum consumer satisfaction and consumer value; and the function of

discrimination, rewarding to those who really contribute excellence,

and penalizing those who do not want to contribute or to risk.

The economic aspects of marketing, according to Holloway and Hancock

[49, p. 11, are twofold in importance: First, consumer's behavior is

influenced by their economic status which creates an environment for

other influences to act upon the consumer. Second, firms act in the

market in a competitive atmosphere with price serving as a signal to

exchange transactions. "In this way the economic dimension is broadened,

and the economic environment of the firm becomes a market force worthy of

consideration" [49, p. 11.


The Role of Marketing in Economic Development


Marketing is an essential consideration when planning economic de-

velopment. Moyer and Hollander [84, p. 2] attribute the importance of

marketing in that process to the fact that it permits increased agricul-

tural output to be moved into commercial markets, and since distribution

systems link markets with markets and producers with markets, these

systems equalize and distribute goods from surplus to deficit areas.

Since producers and consumers are separated geographically, production

and consumption cycles are different, food products though harvested








intermittently are consumed at fairly regular intervals, and the neces-

sity of marketing agents is evident to keep goods Flowing both geogra-

phically and through time. The economic development process will suffer

if this distributive function is not well performed.

King [64, pp. 78-9], in analyzing the ir.portance of marketing in

economic development, states that it is desirable that farmers respond

to prices and income incentives for three goals: a nutritional goal,

a price stability goal, and a growth goal. Inefficiencies in the pro-

duction of marketing services and in the pricing system interfere with

the achievement of such goals. Three basic conditions, according to

Abbott [3, p. 5], are of special importance in assisting market demand

to provide production incentives: reasonably stable prices for agri-

cultural products at a remunerative level, adequate marketing facili-

ties, and a satisfactory system of land tenure.

Despite its apparent importance in economic development, late

emphasis on marketing may be due to the centuries-old belief in the

unproductive nature of marketing and middlemen or possibly to the

belief that marketing is an accommodating mechanism and that firms will

appear to provide the necessary services once the need for such services

has been felt. Collins and Holton [16, p. 360] have demonstrated the

erroneous nature of the latter point. They emphasize the need for special

attention in transforming the organization and operation of the distri-

butive sector rather than the physical facilities.

Abbott [I, pp. 87-8] attributes the neglect of marketing in de-

velopment plans to two possible causes. One is the belief that a

laisez faire attitude will better solve problems than if solutions are








included in a plan. The other possibly is the ignorance of planners

about the importance of marketing or their lack of interest in the

subject. Going to the other extreme, there may exist the temptation

of giving marketing an over emphasis and without sufficient attention

to production. Heady and Mayer [45, p. 31] have already given warnings

about this tendency when they state that both the producing and the

marketing sectors should be considered and tackled together. Two

opposite examples of imbalance are: (1) the case when increased food

production is penalized in the market and the production potential is

not realized because consumer preference places a low value on the

commodity; and (2) the situation when large investments of effort and

funds are made in marketing research and facilities without relating

these investments properly to production conditions.

Times and attitudes about marketing and development are changing

as stated by one author who writes..."countering the crude notion of

the non-productivity of marketing is the growing realization that the

activities performed in transforming farm products in space, form, and

time are a useful and necessary part of the economy" [34, p. 132].

This growing consensus conveys the idea that changes are needed not

only in the distributive sector to help the development process, but

that this sector can actually play a leading role in that process.

Collins and Holton [16, p. 360], in arguing against a passive role

for marketing, state that the distributive sector can under certain

circumstances play a very active role by changing demand and cost

functions in such a way as to encourage the expansion of the agricul-

tural and manufacturing sectors. Rising productivity, according to









Fletcher [34, p. 132], creates demand for services produced by different

marketing firms and the strategic position of the distributive sector

gives it a leading role in development. He further argues that in LDCs

there is a need for a relatively heavy emphasis on technological effi-

ciency as contrasted to economic efficiency (consumer satisfaction is

more important than consumer sovereignty) and that the marketing system

is the necessary connecting link between consumers and an increasing

volume of food and fiber production.

There are many variables influencing the distributive sector in

LDCs. An important publication [67, p. 5] lists the following: the

stage of technology in its agricultural production system and in its

overall economy (the rate of agricultural growth); how well the country's

domestic production can meet the country's food needs (the extent of

the dependence on external food aid) and the extent to which a few

crops make up the bulk of the people's food supply; the extent of ur-

banization; the level and distribution of income, and the income elas-

ticities of demand for food; the size of the country, the population

distribution within it, and the rate of population growth; the country's

socio-economic structure and its politico-economic ideology (the environ-

ment for private investment and the ease of entry into marketing enter-

prises).

Many authors have made important contributions about the role

played by the variables that influence the distributive sector and the

contribution of this sector to the process of economic development [I, 2,

3, 4, 5, 13, 14, 16, 18, 28, 31, 34, 40, 41, 42, 43, 44, 45, 49, 57, 64,








66, 67, 73, 79, 81, 83, 84, 86, 88, 90, 97, 100, 102, 103, 104, 105,

110, 112, 115]. Drucker [28, p. 344] assigns marketing such a criti-

cal role in the development process as to consider it to be the most

important "multiplier" of such development. Though often neglected,

market system development makes possible full utilization of existing

assets and the productive capacity of an economy, mobilization of

latent economic energy, and development of managerial talent.

Moyer [83, pp. 7-19], however, summarizes well the existing litera-

ture in several propositions about the role of the marketing sysLem and

marketing institutions. He suggests that they can provide the necessary

means to coordinate production and consumption and provide consumers with

the commodities they need and want. By making available new or improved

products, improved marketing systems can increase the elasticities of

supply and demand. Market systems can also reduce risk by providing

more adequate information flows among participants in the system.

Secondly, markets can incorporate subsistence producers into the ex-

change economy and also be an important channel for entrepreneurial

talent and capital for other sectors of the economy. Third, as a

result of market extension, market systems may generate pecuniary

and technological economies, both internal and external, for producing

firms. Efficient markets can lower consumer costs by improving dis-

tribution efficiency, more intensive resource use and less spoilage.

They can also reduce transaction and exchange costs between producers

and consumers.

Most important, and closely related to the problematic situation

in this research, is the fact that marketing can "produce" just as








farming does in the following senses: reducing losses to consumers

is the same as increasing yield; storage augments production for the

off season; providing timely inputs to farmers also increases yield;

improving quality increases value (price) though often for marketing

agents beyond the farm level.

Transplanting marketing strategies from the industrialized

countries to the developing countries should be avoided. Currie [18]

has shown that it is ill advised to assume a standard pattern of de-

velopment for all countries and that trying to apply the marketing

organizations and techniques of the developed countries to LDCs will

not render satisfactory results. This is due to an array of differen-

ces in marketing efficiency between the two groups of countries ac-

cording to Chaturvedi [14, pp. 118-23]. While in developed countries

the producer is relatively prosperous, and is linked to and depends

upon, the market, the self-subsistence farmer of LDCs is not. While

in the advanced countries the main source of income of the middlemen

in marketing is their turnover profits, in LDCs the often numerous and

small middlemen generally depend on their margins for their incomes.

Differences in transport and communications, information, storage,

grades, and standards, etc., also prevail between the two types of

countries. For these reasons it is clear that a transplant of tech-

niques from advanced countries to developing countries will not

necessarily produce satisfactory results. In traditional economies,

on the other hand, marketing firms play a passive role by merely

buying and selling. They can be positive and play a major entre-









preneurial role. Development of the banana marketing industry in the

United States started by a ship owner looking for products to haul

back to the U.S. from Jamaica who was later joined by other food mer-

chants, is a good example.


Marketing and the Theory of Demand in LDCs


A special consideration must be given to the relationship between

marketing and the theory of demand in developing countries. The impor-

tance of the application of demand theory to developing country problems

is accentuated by the introduction of new technologies coupled with a

complete lack of knowledge about demand conditions for the different

commodities. The excessive variability in the quality and volume of

supply can be a tremendous problem for producers and market organizers

in these countries.

The law of demand states that, ceteris paribus, quantity demanded

of a commodity varies inversely with price. Chaturvedi [14, pp. 131-2]

has pointed out several reasons why the law of demand can present special

characteristics in LDCs. The law of demand assumes that conditions re-

garding the means of transport and communications are similar everywhere.

Nevertheless, it sometimes happens that in LDCs, when transport diffi-

culties occur, price increases are present when demand in a region has

risen even though supplies of the commodity are adequate. Another

characteristic present in LDCs is the fact that, particularly for food-

grains, movements of some commodities follow the directions of the profit









trends or the expectations of the middlemen without considering con-

sumer needs. This may result in surplus in one area while there is a

need for the commodity in another area which lacks the necessary pur-

chasing power.

Knowledge of demand conditions are of foremost importance for

planning in developing countries. Abbott believes that

...the first stage at which market considerations enter the
planning process is forecasting probable demand as a basis
for fixing production targets. While looking for potential
resources to exploit is one of the first elements in any
plan to accelerate economic growth, decisions on how to
use these resources and at what pace to put their products
on the market must depend on an appraisal of the demand.
This includes both the demands of a growing domestic
population and the demands of international markets in
which a country hopes to sell as a means of earning the
foreign exchange it needs for development...Where less
familiar or more specialized crops enter a plan, care-
ful attention to consumer tastes, preferences and habits
is essential. Examples of misjudgement on such grounds
are common [1, p. 94].

It is necessary, however, that the market demand provide production in-

centives. Of special importance are, according to Abbott [I, p. 102;

2, p. 365], first, reasonably stable prices (without discontinuous

intra or interseasonal changes) at a remunerative level. Farmers will

hesitate before incurring additional work or expense to increase pro-

duction unless they have confidence that prices will be higher than

costs. Second, adequate marketing channels and facilities must be

provided at the proper time. Farmers will be disappointed if they see

that their increased ouput cannot. be sold due to the lack of a proper

channel. Finally, a satisfactory system of land tenure avoids

large share of the returns from increased output going to the hands of

the landlords.









To avoid marketing problems in the future, research on demand

conditions must be conducted. This should include both domestic

and foreign demand. Knowledge of price and income elasticities of

demand can be used to signal producers where, when, and what products

they should produce.


Marketing and the Theory of Supply in LDCs


Of special interest to our concern about traditional and commercial

farms and crops'response to improved technology is the relationship

between marketing and the theory of supply in developing countries.

The law of supply states that, ceteris paribus, quantity supplied of

a commodity varies directly with price.

Developing countries often emphasize increasing production of food

crops by relying on modern yield-increasing technology. Adoption of

the new technology is supposed to foment increased productivity and

production [26].

Technological advance, however, may bring about productivity in-

creases yet the same level or declines in aggregate production. Due

to major seasonal and cyclic price fluctuations mainly in basic grains

and to small farm income limitations, small farmers in LDCs choose,

quite rationally, to grow only enough of some food crops for home con-

sumption. Policy makers often desire to secure for the country adequate

increases in the marketed supply of food crops and to determine necessary
2
future changes in land utilization to meet that objective. Knowledge of




2The impact and implications of foreign surplus disposal in develop-
ing countries are voluntarily ignored. The interested reader is referred
to some of the relevant literature [33, 62, 63, 91, 109, 111, 121].









total and market supply response by traditional and commercial farms

to changes in production, price and income under different regional

conditions has concerned numerous development economists. Major

contributions to an understanding of the forces governing supply

response in "subsistence agriculture" are provided by Wharton [119],

Behrman [Ill, and Krishna [68, pp. 497-547].3 The latter has pro-

vided a comprehensive analysis about agricultural price policy and

economic development, mainly concerned with supply response and price

determination in developing countries.

The behavior of farmers in developing countries relative to a

marketable surplus has been the main focus of several recent more general

studies. Included in this research are the relationships between mar-

ketable surplus and dual development [23], marketable surplus and eco-

nomic growth [29], and marketable surplus, dual development, and economic

growth [122]. The relationships between marketable surplus and price

[60, 72, 114], size of land holdings [87] and stages in the process of

development [78] have also gained special attention.

Numerous specific studies related to production and supply of tra-

ditional and commercial crops, annual as well as perennial, mostly con-

cerned with estimating the sign and magnitude of the price elasticity of

the marketable surplus, have been conducted [6, 7, 8, 9, 10, 15, 20, 21,

38, 39, 50, 60, 61, 69, 70, 71, 76, 77, 85, 99, 113, 116]. The results

generally suggest that the inverse relationship between surplus and



The author does not want to discuss the acceptability of using the
concept of "subsistence agriculture" so broadly. Miracle [82] considers
the use of the term erroneous since agriculture in LDCs, according to
him, is not homogeneous.









price found in some cases can be attributed to two possible causes.

One is tied to the relatively fixed demand for money by traditional

farmers which calls for sales only to the level of money needed. The

second cause is that increasing traditional crop prices may stimulate

an increase in the farmer's income such that the income effect on his

demand for consumption of the crop outweighs the substitution effect

in production and consumption [73]. For either cause, marketable sur-

plus may be inversely related to price.

A very important recent contribution by 'iens [120] adds risk to

the picture. Wiens, using quadratic programming to examine the impact

of yield uncertainty on peasant allocation of land among crops and

their use of hired factor services, shows that optimization qualified

by risk aversion proves superior to risk neutrality or credit constraints

in explaining peasant allocative behavior.

Despite the growing interest on small farm agriculture [12, 94, 82]

the research on supply response in traditional agriculture seems incom-

plete. A definite explanation of the two causal phenomena producing a

possible negative relationship between surplus and price has not been

provided. Nor has there been an explanation of why the response situa-

tion happens in some but not all regions of a country, or how one can

predict and measure the effects of that behavior. To complicate the

situation even further, after contemplating their research results on

the subject, Manghas, et al. state that price may not be very effec-

tive in increasing aggregate agricultural output, which implies "a much

less optimistic outlook for the role of price as a development tool, at

present levels of technology, than if price changes induced yield as

well as area changes" [76, p. 635].





55


The need For a theoretical and analytical framework to enable

economists to analyze the total small farmer basic economic system

is evident. Such a framework would be an important contribution to

the development theory. This research attempts to provide a basis

for more fully understanding supply response criteria inherent to

traditional and commercial agriculture in developing countries.














CHAPTER III


THEORETICAL AND METHODOLOGICAL FRAMEWORK FOP INVESTIGATING
TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE


The basic economic system of the Guatemalan small farmer is described

in the first section of this chapter. A second section contains the

method of estimation with the corresponding hypotheses and equations

and the description of how the model has been adapted to the different

regions of the country and the different cropping patterns. The third

section explains the methodology used for computing input acquisition

and product disposition. Finally, data used and implications are briefly

discussed.


Basic Economic System of the Guatemalan Small Farmer


The environment in which a Guatemalan small farmer lives determines

his consumption and selling decisions. A small farmer grows basic grains

mainly for home consumption. At harvest time he disposes of his produc-

tion in several ways. A large share is kept for family consumption and

other noncash purposes such as feed, seed, payments in kind, etc. If

cash is needed, part of the output may be sold at the time of the har-

vest. In good years some production may also be saved to be sold through-

out the year whenever the farmer needs cash or when high prices make

selling worthwhile.









The hypothetical price-income-consumption (PIC) path developed

in Figure 5 (A) illustrates the small farmer's consumption and selling

decisions and is used to develop his market supply curve for a product.

Due to his subsistence needs, the small farmer's demand and supply

situation for items produced on his farm is somewhat unique. Figure

5 (A) shows a hypothetical price-income-consumption (PIC) path for a

commodity produced and consumed at the farm level. Assume the. farmer

is at point Z, where price is P and increases to Pb. The farmer's

income will increase. The income effect created by the price increase

will make him move up and along the PIC path. Most food crops pro-

duced on the farm can be considered as inferior goods; since small

farmers usually have so little income, a small price increase may pro-

duce a significant change in his income position such that he is willing

to consume less of the product. Since he is his own supplier, he can

cut back on his consumption. If the process is repeated, the hypothe-

tical price-income-consumption (PIC) path shown in the figure can be

drawn. Total output is fixed at OB and the amount OC is the minimum

necessary for family subsistence and seed for the coming season. If

quantity OB is desired for home consumption and other noncash purposes,

the farmer will not sell any output. However, cash needs or higher

prices throughout the year might induce him to sell some of his pro-

duct and forego some consumption. For example, if the price is PI, the

farmer keeps OA and sells AB.

The decision process at harvest time and for the short-run, depicted

in Figure 5 (B), is dependent primarily on product price, home consump-

tion needs, and cash needs to purchase other goods. At harvest total
T
supply is QI If the price is Pi, the farmer expects to consume OA1













I

Pt I

P


Pb
_ -


OC A


- PIC


B Q


(A): Firm--Long run price-
income-consumption path


PIC


O C A2 AI B2 BI Q

(B): Firm--Short run home vs.
sales


I --P' IC I I I
O C Q 0 AB C D MT Q
(C): Industry--Price-income (D): Industry--Market supply
consumption path
Figure 5.--Guatemalan small farmer consumption and selling decisions









H 1
(QH quantity used at home) and to sell AIBI (Q quantity marketed).

This decision at harvest time establishes OAl and AI B as supply and

demand proportions for the year if price stays at P When all of the

output is sold at harvest, no further decisions are possible. If the

farmer did not sell everything at harvest, Q2 becomes the new fixed

total supply curve since B2B Iwas sold or consumed. At P expected

home use would remain at Q1. However, as price rises to P2, home use
H
declines to Q2 or 0A2 and sales are A2B2 thus reestablishing demand

and supply proportions. The process, when induced by increasing

prices, may continue until Q reaches the amount where the hypothetical

price-income-consumption path becomes asymptotic to th2 Y axis at OC,

the minimum needed for family subsistence and seed. It may happen

that, as QT shifts to the left during the marketing period, prices

above P2 result in decreasing quantities marketed. Little or no surplus

available when prices keep rising may bring about indirect relationships

between prices and quantities marketed. For price declines, the process

is also operative and illustrates greater home use relative to sales for

the short run or one season.

From the hypothetical price-income-consumption path for each small

farmer, as illustrated in Figure 5 (A), a community of price-income-con-

sumption paths can be developed as in Figure 5 (C). The effects of price

and income changes, (e.g., constrained variables) result in movements

along the path. Other variables exert an influence in the position of

the PIC path. While increases in farm size and in the level of education

with other things remaining equal, make the path shift downward, the

opposite occurs as distance to the market and quantity demanded on the

farm increase. If the profitability of other grains goes up, the PIC








path also shifts upward. As the PIC path approaches the total production

constraint (Q ) it becomes more elastic. At point Z, the elasticity of

the PIC path is infinite; price is so low at this point that farmers

decide to consume everything they produce since there is no incentive to

forego consumption through sales in the market.

The hypothetical PIC path is used to derive the market supply (Q)

shown in Figure 5 (D). By starting at point Z and moving up and along

the PIC path, quantities marketed at different prices can be read to
M H M
establish Q If the quantities used on the farm (Q ) are added to Q

the total quantity produced (Q T) is identified.l At this point, Q does

not present the completely vertical shape that the fixed total supply

curve shows in sections (A), (B), and (C) of Figure 5. Although Q is

a fixed amount until the next harvest, it does decrease during the mar-

keting period as the farmer alters his consumption and selling decisions

due to changes in his income situation produced by price changes. For

that reason, when QH (OC or MT)isaddedtoQ QT slopes upward. At P,

however, both annual supply functions (QT and QM) are perfectly inelastic

and will not be affected by further price increases. Here the basic

identity Q Q QH will not be subjected to further alterations until

the following harvest. Since there is an infinite number of hypothetical




Income level and farp area devoted to the crop in question provide
offsetting influences on Q which are not measured in this research. As
income rises with an income inelastic demand for a basic grain, consump-
tion per capital at the farm level may decline while demand for seed may
expand until the income supply response function Q becomes perfectly
inelastic. For this reason a fixed Q is assumed.









price-income-consumption paths, representing numerous farm families, and

of combinations that can be made between Q and Q and since Q shifts

over the marketing period, there is an infinite number of possible Q
M M
curves as shown by Q to Q in Figure 5 (D). Since Figure 5 (D) is
1 n
derived from Figure 5 (C), the starting points of all industry supply

functions are completely elastic; such a low price does not induce farmers

to market any output.

Assuming that Q and QT in Figure 5 (D) are two observable supply

functions, small Farm market behavior can be further investigated. At

price PI, OT is total quantity produced (QT ), AB is the quantity kept at

home ( H) and OT minus AB is the quantity marketed (QM). As price goes

up, QH will fall until it reaches the minimum amount MT. At P2, for

example, OT is again total quantity produced (QT), CD is the quantity

kept at home (QH), and OT minus CD is the quantity sold in the market

(Q ). Q is therefore not a fixed amount but becomes a function of price

throughout the marketing period. Thus, knowledge of those conditions

that induce changes in QT and QM are necessary to identify both curves

and the implications of their relative locations and shapes.

Since the levels of QH observed are not actually purchased in the

market at different prices, we cannot obtain farm family demand func-

tions, final equilibrium points, and demand elasticities. Interest,

however, is in determining supply responsiveness to changes in farm

size and level of income.

Enterprise combinations utilized by small farmers at different

income levels are closely related to the theory of small farm demand

and supply of basic foods. More specifically, the impact of income

changes on the relative quantities that are produced and marketed from









the crop mix as well as land use patterns support the demand and supply

theory. This subsistence, land use and crop mix environment of the

Guatemalan small farmer is characterized by varied levels of risk

aversion as relative incomes change. With few, small and divided plots

of land at his disposal, the small farmer grows primarily traditional

crops although he may also produce some commercial crops where risk is

minimal relative to that of other high value crops. As opposed to low

risl traditional crops grown mainly for subsistence, low risk commercial

crops are a source of income where adversity would not extend beyond

normal weather fluctuations. Low risk commercial crops may also include

crops whose prices are supported by the government. Wheat is a good

example for Guatemala.

The small farmer's behavior within his basic economic system is one

of carefully balanced risk aversion, income maintenance and risk taking.

As depicted in Figure 6, at very low levels of income or farm size the

farmer grows basic grains for subsistence though he may also sell part

of his production. The difference between total quantity produced (Q )
t

and quantity marketed (Q ) of a traditional crop depicts home use re-
t
quirements for consumption, seed and other purposes (Q ). Since crop t
t

is mainly intended for subsistence, the curves show some income respon-

siveness at very low levels of income and almost none at high income

levels. Because some grains will always be grown due to cultural values,

(corn and beans are good examples), the curves will be similar in shape

and, once the home use requirement is reached, the curves will tend to

become perfectly inelastic (or vertical) regardless of income level.















T
Q
I t2


T T
c T Q
2 c
T
Q
cl


0 Quantity of basic grain
Figure 6.--Income-quantity or farm size-quantity relation-
ships for the Guatemalan small farmer, given his
land constraint


Income
or
Farm Size


12
lt2


5


~
=I


Q I
M C,
Qt









As income rises, due to productivity and/or price reasons, the farmer will

divert some of his land into other commercial crops (Qc) while maintaining

his self-sufficiency productionon less land. In this case, the response

will increase with income up to the point where the farmer has no more

land available for crop production or it is feasible to introduce another

commercial crop.

Thus, as income rises, small farmers with their self-sufficiency

guaranteed, will tend to diversify production by growing high value crops

until the land constraint is reached. Qc in Figure 6 is not produced

until a certain minimum consumption and income level is attained with the

basic and low risk crops. Income responsiveness of the higher value and

higher risk crops is greater than for the traditional crops. At higher

income levels farmers venture into higher risk crops and combine their

production according to income level and land availability. Figure 6

is also operative to determine land use patterns when the vertical axis

is labeled with different levels of farm size.


Method of Estimation


This section presents the methodology used in this study. The

hypotheses to be tested with the corresponding functions and the adapta-

tion of the model to the different regions and to varied cropping patterns

are also explained.


Hypotheses


Since income-supply relationships are the main focus of th;s research,

the primary set of hypotheses relates to the respective elasticities. The









hypotheses are formulated broadly since it may be the case that a tra-

diticnal crop in one region may be a commercial crop in another region.

The functions, and corresponding elasticities, will behave differently

in each case.

Concerning income elasticities of market supply it is hypothesized

that:

(I) When crops are grown for subsistence, at very low levels

of income, small farmers will market very little. As

income rises small farmers will market more but only up

to a certain amount where they have their self-sufficiency

secured.

(2) If the income of small farmers rises, they will produce

and market successively higher value crops in combination

with subsistence crops and within their land constraint.

Concerning the productivity of basic grains and of competing or

alternative commodities, it is further hypothesized that:

(3) If the productivity of basic grains grown for subsistence

increases due to yield-increasing technologies, then small

farmers will produce up to the point where they would have

their self-sufficiency secured with less land.

(4) At low income levels, as alternative crops become more

profitable, small farmers will produce and market wheat

up to a certain amount after which they will shift to

other commercial crops since their income cannot be

increased much more due to the wheat price support limit.








Concerning farm size elasticities of market supply, it is hypothe-

sized that:

(5) When farmers are at the very subsistence le',el, all aJail-

able land is devoted to traditional crops. As technology

or farm size continues to increase, small farmers will grow

other crops while maintaining their self-sufficiency.

Concerning price elasticities of market supply, it is hypothesized

that:

(6) As the price of basic grains rises, small farmers will

market more output but the percentage increase in supply

will be less than the percentage increase in price.

Concerning production and distribution activities of traditional and

commercial basic grains, it is hypothesized that:

(7) If the productivity of basic grains can increase, and

production gains are obtained at the same time, production

and distribution activities can still be performed adequately.


The Model2


Based on the small farm decision process just described, the following

market supply function can be estimated:
M T 1
(1) Qi / QT + P i +P + E + A. + 4 D. + 5 'i + 6


W. + i Y. + c.




2The Appendix contains a complete specification and discussion of
the mathematical and statistical models.









where,
Mi T
Q. / Q. = percent of grain production that is marketed (kg);
I I
P. = farm price of basic grain i (quetzales/kg), and estimated
in reciprocal form;

E. = education of household head (number of years of formal
education);

A. = total farm size (ha) and estimated in reciprocal form;

D. = distance to the nearest market (km);

I. = quantity of basic grain i demanded at the farm level
for all purposes (kg);

W. = return per hectare in all basic grains except, basic
grain i divided by return per hectare in basic grain i;
and,

Y. = total family income (quetzales/year) and estimated in
S reciprocal form.

The reciprocal is chosen for P., Y., and A. because in the theoretical
I I I
presentation the function is hypothesized to slope upward and to become

perfectly vertical at a certain point. Complete inelasticity occurs in

the case of price, when the farmer does not want to sell any part of the

quantity saved for home consumption and seed; in the case of income, when

the subsistence level has been achieved; and in the case of total farm

size, when other crops enter the production system. The rest of the vari-

ables are estimated in direct form.

The ratio of marketed output to total output (QM / QT) is estimated
i T
instead of Q. alone because Q. becomes a different constraint, based on

farm size, for each farmer. The quantity retained for home use varies

considerably among farmers and crops and only a certain maximum percentage

of total supply can be marketed. In a totally commercialized farm, the









ratio equals one, while in a totally traditional farm it equals zero.

A positive sign indicates that the crop becomes more commercial as inde-

pendent variables increase while a negative sign indicates a tendency to

more traditional, or less commercial crops for the direct variables (E.,

D., I., W.) and the opposite for the reciprocal variables (P., A., Y.).

The ratio also beco.nes smaller or larger at different price levels due

to the total production constraint.

Total farm size (A.) is included instead of area producing each

crop (A.) to account for the differences in farm size and to illustrate

variations in quantities marketed at different levels of farm size.

Therefore, the same observation (A.) per farm is used in the equations

for each basic grain regardless of the amount of land devoted to its

production. The weight (W.) should account for the different basic

grains grown by the farmer and, therefore, any possible substitution

among them. The rest of the variables are self-explanatory.

Price (P.), income (Y.), and total farm size (A.) will carry nega-

tive signs if the function behaves as postulated. Quantity demanded at

the farm level (I.) is also expected to carry a negative sign. Distance

to the nearest market (D.) and education (E.) are expected to carry

negative and positive signs, respectively. The relative profitability

ratio (W.) will carry a positive or a negative sign according to the

traditional or commercial nature of the crops in the region.
M T M T
Once Q. / Q. is estimated, both Q. and Q. can be obtained.
I I I
From the theoretical presentation we know that

(2) Q = QM + I
I I









From (1) we can write
M QT. QT
(3) Q' = Q /i QT or

(4) Q = Q (Q / QT) + I. ( / QT)

Solving for Qi'

(5) Q. / Q) = / Q

Final ly,
M M T M
(6) Q. = ( / Q / (1 Q / Q)

Once (6) is obtained, it can be substituted in (2) and, after adding

I., Q. can also be obtained.
I I

Adaptation of the Model


The model is adapted to specific circumstances in different regions.

For example, when two crops are associated, Q. / QT for both crops must
I I
be estimated. Price and quantity variables must be converted to weighted

values to permit realistic comparisons and derive realistic conclusions.

In the case of two or more associated crops the following weight is used:

Let TR. and TQ. be total revenue and total quantity of crop i, respectively,
I I
and TR. and TQ. total revenue and total quantity of crop j associated with
J J
crop i in one region.

Then,

ETR. / ETQ. = P., a weighted price for crop i in the region, and,

ZTR. /ETQ. = P ., a weighted price for crop j in the region. Then

M T [M/ T and
Q.. / Q.. may be estimated as the sume of P . / Q ] and
I.J and\









P [Q / Q.1, and Q. / QT. will have been given a value figure. In
j J J ij i
the case of price on the right-hand side of the equation, (P. Q + P.
I I J
Q)/ (Q + Q) = P.., a new enterprise price for an association.
j j Ij

Production and Distribution Activities


Description and quantification of production and distribution acti-

vities is illustrated in Figure 7. These activities are explained for

every enterprise in the different regions of the country.

The figure contains amount (kgs) and cost (quetzales/kg) of the

different inputs utilized in the production process and the different

ways for disoosing of total production. Since figures in each cell take

into account the weight given to each questionnaire, they are intended

to represent good approximations of totals in the region.


Data Used and Implications


riot all farms contained in the sample are used in each of the esti-

mated equations. Q. / Q. picks up only those farmers selling some of

their output; or in terms of the theoretical presentation, those producing

more than OC in Figure 5. Furthermore, it seems that the sample failed

to include a considerable number of these farmers, and, since the sample

was intended for a small farm study, only very few of the large farmers

were included. For those reasons, the estimates are conservative. Re-

sponses will therefore be stronger than shown in the results since both

ends of the spectrum are not considered. In Chapter six, a special

section is devoted to the discussion of the descriptive statistics of

each independent variable, and generalizations and implications of the

results.



















=)





C

U





0


CD


u


U

a(
c3










-0
L





0
l)




ro

o






C


0


O--
-o



U

L-


CL










0
CI

















OC




0)
-O
L-I



0 3.













L
-- t-


p, C
L)0









The computations of the production and distribution activities do

encompass all farmers in the sample size. For that reason, averages in

the activities, especially total quantities produced, may not coincide

wicn those in the estimated equations.


Summary


This chapter has described the theoretical framework which explains

the Guatemalan small farmer's behavior within his basic economic system;

a system in which his subsistence needs, the land constraint, and his

income level are the most important variables. The production and dis-

tribution activities to be described and the equations to be estimated

attempt to quantify that behavior by considering the variables that may

be relevant to his decision making process. The degree of success

achieved in quantifying that behavior is the subject matter of the

following chapters.













CHAPTER IV


PRODUCTION AND DISTRIBUTION ACTIVITIES


Production and distribution activities for each basic grain or

association produced in the different regions of Guatemala are described

and quantified in this chapter. The description by crop, or association,

follows the pattern of analysis utilized in Chapter five. Characteristics

or each crop or association are identified for each region to facilitate

interpretation of the results presented in the remainder of the disser-

tation.


The Input Market


Input use in basic grain production is presented in Table 8. After

briefly defining each production activity, the description focuses on

the relative importance of each activity across enterprises and regions

(Table 9).


Seed Utilization


The activity of seed utilization relates to the total amount of

seed purchased at planting time or stored from a previous harvest.

Some differences in seed management across regions and crops are

present. Of all the associated enterprises, corn-beans in R5 and R6

73


























L\


02 0'. CN
CO tri rd
7. r-
C0 LA .n

G1 Lt\ 0
..T 0



c. r- rO-

CC.


'D -7 -



000
CD C- LA




-T r-. f~




-3 -3l r,
co C. 0"




o
0 LP1





0 Ci
0 rN. Co


L\ -






-0
- O















'r. C.4
C-. r i
co *r%




















rl: O
(N. C 0
L, (N r -



LA




.r. 10 cc,




S- 3


-O
0

u 0











CC
c C
0. J -











cJ L 0
I.

0 C CC 0 0
C C'. -3-
,.O. ('


Cr- 0 0 0 0 o-
00 rC0 C -
o -o r":

C. -7
-3_




C.LA 0 0 r...-- co -
-3. co -.. rJ rC.


N N





rL CO r N r C en
co ci o cl -





cu o -i o











E 0 E E N 0 0
-< O < O -C CM i

uu N







OO C u-

E OE DED
L < 0 C 0







< L 'J: Li < Li Li Li


0 rN.

00

0 --
rcN


0
.-
LD. \J
O'i




LC,


L.


Q 0 0 0 03 .N4 Co 0
lN %D ID C-% CS. r4
L- Or 0 CN M

LN CO 0 O uN
o Cs LC L-A
NCM -Z



cs o 0 C) N- r. CO


0 o -0r0 -
cc C-3. CD
c-%



C4 o -3 cl% (- r C 00
C. L0 -c CC : oC. c. -

-7 7'. C- -.7 CO 0I.
NJ C- 'D rO n
- ULN


- L\ CO C1 0 I0 C0l cc
r CO r C 0O -3- r. -
0o co C .. rC co 0

co cS r~ C. -r3
C. Lr -



0 -3 00 C0 0 -




0 \0r CO

SL 0 r0 N. -
r r- -.\






0 rn CO -




- Ln- -


C I












Ln








S0
0
























40
I











--
.11




u





C
















NCO r. C0 0 000 L
-.J c- :D : 0-%0o o ;; "
-3L LD 0 \ CM L
a' D -s-. o^cr Q.








m .--- n. -- 3
CNI 00 Z 0 1 OD O 'r.0 CN
-O rCDn -rr4' MO o o r- -T
Oi cr co LnN cLr o r"a C3 m n





.Lfl L C) 0 -T C
C C



-0 - N -" 0 --
"> CMT 0" co




cN0 0000 00- .
:T r4 C CC. C'P, Lf C,). .-T Cr




-- cN O 0
I u E















ID
-Oo ,- c f- -- N- -.
oc m M rLA E^ iM m ^o r3 o










N- -- LU o0


0W M 0









rI _
70c-O 1-fiOt co-PL')- L








3na Lm -r Ln z" C'
r p o CL





N O

OCN 01) 0L aN m


O" C-4 oN-- -l C- m
S N LE CL

-C

C-l -T' -oToo C iON'. o .C c
cN U. C o- %D -T o -0 ,


-. 0 -
M -- L c>






0 L0 ," 0" C O 0 )
'4 0 U) IN3 -, r-C i. >L
0-- - i
UI- 1.













I a "-O "-- ---
CN
in O






C 'V


'.0 I 00 01q 0 O 'o
Un --INTO .3'.M U co CU -
- -- -E
n -D t~ 0.
-' o c



-U -
( -r ro C






in0 a) c
0 CI -
~P -C


C ol E I D Dn


M u 9 0 M 0
c a 0 0 t C u
1V C Li u 0 O3
*- If) .- 3 < UlJ JLJ . -j





'" ~ ~ v cu i r Euu~u o Looot













- LT. -




CO (C -3



-T r-.
C0 -











-3 -3 LJ.%
- Lr.


rn r- (N








In0 r( --


F- -L.

'D ..co
S-Ln-
\D(NM










C0 GD 0




r.











SLT. Lr.


'3.0-7





CO r-~
r( Lt.



- rN
LrU CN


- co
LT-. .3


L%
-U-T


--0
- GD

GD (N






-Zr'-
U\\D



;L G
C iTr.











- 0
CM4 U"%
(N L.A

- n


e30)
co r.co









-'.0








r, -3
CM4 Lr.


IT. CM









N0








(N










UN -









N
S-




a-, -









Com
r--













10 0%
0rIN


00





NN


00




C) 0



00



00



00



00



00



00



00



00




CC






00




00






00





0 0
o' ol



Co C




C),C






Co





Co C


(N CIN c
NCCO
I- N

04
V


m 0







Su 0u
LCJL)








ci 4) I~
P3VI






Ul C-.
01 c U'


L_ ID I
*Ll a .-I
a 0




DUOI
C)l^
c,, c-. c

LLU

> >CL


CN CN


ci r-




S0
I.'*








l I-

a>



,*-




LU


- 13
U 4)
Hi-C
L









cu Ca
en cn



> >
Ci 4)


.O
I-I




-c
U





.C
*r-





L L
, 0
:) u
















O D LD





cf -3 CO





- C. N




00



























Ln



L A
- L J




































rC
- CM, ,










3 O C









CO
n-

















O -
t o


- -T




L. L


U U
0 0







n L-
L L

O >
a C


0 un 0
0 0




> 0 >
< .- <


0r



Ln 1




L CD
Ln
-c





01
0 0






ED


Cn
ON






L
r




OO
Cu
U 0


C

( >
E- L











.L
un









aC


U
L C





En
0
*- 0.













C
L L.







C'a

E
-i

























L.
En
010

dn











1U



it 0
L.







-

Ea .









*-
CU



-. L


a


U'







U




a
c








is the heaviest user of seed per hectare. Corn-beans in R and R is

most dependent upon stored seed.

Land scarcity in RI calls forth more intensive production of

corn and beans as single crops, evidenced by the highest application

of seed per unit of land. This region also depends more on stored

corn and bean seed than the remaining regions.

In rice production, average seed use per hectare is higher in RP

than in R5 and R4 while R5 depends more on purchased seed. The main

difference found in wheat production is an almost complete dependence

on seed purchased in R6, as opposed to an even distribution in RI, the

latter being a more subsistence region that the former. Also, less

wheat seed is used per hectare when it is purchased than when it has

been stored.

In general, seed becomes linked to product sales, seed storage,

and seed purchase decisions. Thus, variation does prevail in the per-

centage of total production retained to be used as animal feed and

seed and that percentage of seed which is purchased (Table 10).


Urea Application


Average amounts and cost of urea per hectare suggest that usage

of this input is fairly common. Although urea application appears

for all crops, except for beans in R,, some of the crops contain

only a small number of observations; these crops are wheat in R ,

corn in R beans and rice in all three regions, sorghum in R and

corn-beans-sorghum in R6. For the remaining crops, no major differences

in either average use or average cost of urea per hectare are found.








Table 10.--Seed purchase and sale proportions relative to total production
and total seed use


CROPa REGION
1 3 4 5 6
------------------------Percent-----------------------

b c b c b c b c b c

C-B 4.8 28.0 --- --- --- --- 5.0 9.0 5.6 46.0

C-S --- --- --- --- --- --- --- 13.4 37.0

C-B-S --- --- --- --- --- --- --- --- 12.8 35.0

C 6.6 2.0 3.5 5.0 1.8 50.0 4.4 41.0 5.4 34.0

B 9.8 15.0 --- --- 5.0 84.0 5.4 38.0 5.8 32.0

5 --- --- --- 1.6 55.0 --- --- --- ---

R --- --- --- --- 2.2 52.0 1.8 78.0 5.3 43.0

w 8.7 54.0 --- --- --- --- --- --- 0.9 91.0

C, B, S, R, and W represent corn, beans, sorghum, rice, and wheat,
respectively.
Feed and seed retained as a percent of total production.
CSeed purchased as a percent of total seed used.








Use levels do differ between associated crops and single crops where

rates per hectare average 47.4 kgs and 119.3 kgs., respectively.


Soil Additives


This activity, with use limited to only four crops, contains

amounts of calcium oxide and other soil correctives applied. The

appearance of only three or less observations in every case signals

the extremely limited use of this chemical input in basic grain pro-

duction.


Other Chemicals


Application of chemical fertilizers other than urea is heavier

than that for any single input as evidenced by the use of chemicals

in all enterprises. Average costs per hectare are the highest in

wheat production in both RI and R and the lowest in all associa-

tions and in rice in R The remaining crops utilize similar amounts

per hectare. Again associated crops utilize only Q9.6 worth of chemi-

cal fertilizers per hectare compared with Q25 for single crop enter-

prises.


Other Fertilizers


This activity encompasses the utilization of other fertilizers,

sprays, etc., which are recorded as an average cost per hectare. Very

limited observations of use for each enterprise confirms the minor

role of other fertilizers in basic grain production.









Pesticides


Under this activity, average cost per hectare of applying insec-

ticides, herbicides, and other chemicals utilized in pest control are

recorded. Although used on every enterprise, pesticide application

is not very generalized among farmers. Average cost per hectare for

pesticide use varies substantially but is particularly high at Q12 or

more for rice in Rq and beans in RI and R5. Most enterprises and

regions display pesticide costs at less than Q5 per hectare. Pesti-

cide costs per hectare for single crops average Q7.1 compared to Q2.2

for associations.


Labor


Labor utilization encompasses all phases of agricultural activi-

ties, from soil preparation to harvesting and marketing the final

product. Since it contemplates cash payments as well as family labor,

the word journal used in the questionnaire is assumed to mean man day.

Except for the associations, where employment per hectare is very

similar, all enterprises show different levels of employment by region.

In corn production, RI and R3 employ more workers per hectare than

R R and R For beans, RI is the largest employer, while R5 and R6

use more labor per unit of land than R4 in rice production. Wheat

production requires more labor in R than in R .

For all of the crops present, RI is the largest employer. Perhaps

this is a result of the subsistence nature of the region. In general,

however, associated crops utilize substantially less labor (44.2 man

days per hectare) than do single crops (75.8).









The Product Market


Distribution of total basic grain production is presented in

Table 11. Emphasis is given to the relative importance of the dis-

tribution activities and the major differences encountered across

crops and regions (Table 12). A brief definition of each activity

is also presented at the beginning of each sub-section.


Total Production


Average production per hectare, differing among enterprises, is

very similar for each particular crop grown in different regions.

Yield differences, of course, are correlated with the nature of the

crop.

For the associations average production per unit of land is very

similar across regions. However, when the same crops are grown alone,

corn and sorghum exceed the association yield levels while bean yields

fall below those of the associations.

Rice production shows no major differences in average production

per hectare across regions. In wheat yields are somewhat higher in R

than in R6 probably resulting from heavier chemical input usage.


Animal Feed and Seed


This item pertains to that part of total production set aside by

the farmer to be used as seed in the future or as animal feed. The

activity is a fairly generalized practice as evidenced by a large

number of observations obtained in each crop, with the exception of

wheat in R6.




Full Text

PAGE 1

TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE IN AGRICULTURAL DEVELOPMENT: THE CASE FOR BASIC GRAINS IN GUATEMALA By Jose Alvarez A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 1977

PAGE 2

A los pequenos agricultores del Altiplano Central que conocT durante mi breve estadia en Guatemala: -A los que perecieron a consecuencia del terremoto del h de Febrero de 1976, como sencillo tribute a su laboriosidad y hospi tal idad; -A los sobrev ivientes de la catastrofe, con la esperar za de que el future les depare la prosperidad que nunca ban tenido y que tanto merecen. A la nostalgia que produce la impos ibi 1 idad de hacer esta i nvest igacidn sobre los guaj i ros de mi Cuba,pero compensado por haberla hecho por los de ese pedazo de America por el que Jose' Mart 1^ s i nt io'' especi al devocion .

PAGE 3

To the small farmers of the Central Highlands I met during my short stay in Guatemala: -To those who died because of the earthquake on February 'tth, 1976, as a humble tribute to their diligence and hospitality; -To the survivors of that catastrophe, hoping that the future will bring them the prosperity they have never had and so much deserve. To the nostalgic feeling produced by the impossibility of conducting this research on the guaj i ros of my Cuba, but compensated for having done it on those from that part of Latin America for which Jose MartT felt special devotion.

PAGE 4

ACKNOWLEDGMENTS In most cases, every research product is the result of multiple endeavors. This one is no exception. Sinceitsvery beginning, many persons and institutions have provided enormous contributions. Without them this dissertation would never have been possible. The list is long as deep is my indebtedness. Special thanl
PAGE 5

topic. Special thanks to my friends in Socioeconom "r'a1 CTA, starting with the Coordinator, Peter E. Hildebrand. His vast experience with the Guatemalan situation materialized in helpful comments and ideas during several reviews of the manuscript. To Pete and Joyce, his wife, thanks also for their hospitality and understanding. I am grateful to the Rockefeller Foundat ion , especial'l y to Joe D. Black, for willingness to finance the original project. And to International Programs1 FAS , University of Florida, for making some funds available at an early stage of the research. The Consejo Nacional de Plan i f icaclon Economica de Guatemala deserves credit for authorizing use of the Farm Policy Analysis data utilized in this study. Russell Misheloff, Daniel A. Chaij, Robert Bartram, and James Riordan, USAI D-Wash ington , facilitated release of the tapes and Carl D. Koone, USA I D-Guatemala , was a most valuable intermediary. My appreciation to Sherlar Irani and Mario Ariet for writing and debugging so many computer programs. The facilities of the Northeast Regional Data Center of the State University System of Florida were used for making all computations. Special thanks to Beth Davis and Ann Ritch for valuable assistance in typing so many drafts and to Beth Davis again for typing the final copy. Finally, and above all, I want to thank my wife, Mercy, for her love and encouragement In both good and difficult times. She and I owe too much to Mario and Nini Ariet and want to thank them for being always there. V

PAGE 6

TABLE OF CONTENTS Page ACKNOWLEDGMENTS iv LIST OF TABLES x LIST OF FIGURES xiv ABSTRACT xvi CHAPTER I INTRODUCTION 1 Setting of the Study I Physical Environment 1 Population 2 Government and Political Subdivisions. 3 The Economy 5 Agriculture 6 Markets and Marketing 7 Foreign Trade 8 Setting of the Problem . 10 Introduction 10 Problem Statement 15 Objectives of the Study 25 Data Source and Data Considerations .... 25 Relevance of the Project. . 31 Organization of the Dissertation 32 II AN EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT . 33 Agriculture and Economic Development. ... 33 Agriculture in LDCs: A Changing Spectrum of Priorities 3^* Agriculture versus Industry: A False Issue 36 The Role of Agriculture in Economic Development 37 Some Prescriptions for Agricultural Development 39 vi

PAGE 7

CHAPTER Page Marketing and Economic Development k2 Marketing Defined ^2 The Role of Marketing in the Economy. . ^3 The Role of Marketing in Economic Development ..... ^^ Marketing and the Theory of Demand in LDCs 50 Marketing and the Theory of Supply in LDCs 52 III THEORETICAL AND METHODOLOGICAL FRAMEWORK FOR INVESTIGATING TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE 56 Basic Economic System of the Guatemalan 56 Small Farmer Method of Estimation 6A Hypotheses 6'* The Model 66 Adaptation of the Model ........ 69 Production and Distribution Activities ... 70 Data Used and Implications 70 Summary. 72 IV PRODUCTION AND DISTRIBUTION ACTIVITIES 73 The Input Market 73 Seed Utilization 73 Urea Application 78 Soil Additives 80 Other Chemicals 80 Other Fertilizers 80 Pesticides 81 Labor 81 The Product Market 82 Total Production 82 Animal Feed and Seed 82 Family Consumption 87 Processing 87 Rent Payments 88 Sales "in Kind" 88 Donations 88 Total Losses 88 Cash Sales 89 Marketing Expenditures 89 Summary 90 vi, (

PAGE 8

CHAPTER Page V TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE. . 93 Associations 93 Regression Coefficients 106 Income-Quantity Relationships 108 Farm Size-Quantity Relationships .... 109 Price-Quantity Relationships 109 Corn 109 Regression Coefficients 110 Income-Quantity Relationships llA Farm Size-Quantity Relationships .... 114 Price-Quantity Relationships 115 Beans 116 Regression Coefficients 116 Income-Quantity Relationships 118 Farm Size-Quantity Relationships .... 118 Price-Quantity Relationships 119 Sorghum 119 Regression Coefficients 119 Income-Quantity Relationships 120 Farm Size-Quantity Relationships .... 120 Price-Quantity Relationships 120 Rice 121 Regression Coefficients 121 Income-Quantity Relationships }2h Farm Size-Quantity Relationships .... 124 Price-Quantity Relationships 124 Wheat 126 Regression Coefficients 126 Income-Quantity Relationshps 128 Farm Size-Quantity Relationships .... 129 Price-Quantity Relationships 129 Summary 129 VI SUMMARY, CONCLUSIONS, IMPLICATIONS AND RECOMMENDATIONS 131 Problem and Objectives 131 Research Findings 133 Production and Distribution Activities . 134 Trad it ional and Commercial Farm Suppl y Response . . .r -^ .' . . . 135 Data Generzal izat ions and Implications. . . . 137 Errors and Omissions in Data Recording . 138 Upward or Downward Bias 139 vi i i

PAGE 9

CHAPTER Page Education of household head 1^0 Distance to the market 1^0 Total farm size 1^0 Total family income 1^1 Farmgate price 1^1 Quantity demanded on the farm. . . . 1^42 Relative profitability ratio . . , . 1^2 Conclusions and Recommendations 1^3 VII REFLECTIONS ON THE THEORY OF DEVELOPMENT 1^7 Introduction 1^7 The Green Revolution: Generation Problems and Small Farm Development 1^9 First Generation 1 '*9 Second Generation 152 Third Generation 153 Suggestions for Further Researcn . 155 Epilog 156 GLOSSARY 158 APPENDIX 161 List of Crops 161 The Mathematical Model I6I The Statistical Model: Its Assumptions and Possible Violations 172 The Regression Model 172 Possible Violations of the Assumptions. . 173 Normality 173 Zero mean 17^ Homoskedast ici ty 17^ Sufficient observations 175 No mul t icol 1 inear i ty 175 Regression Results 177 REFERENCES 200 BIOGRAPHICAL SKETCH 211 IX

PAGE 10

LIST OF TABLES Table Page 1 Guatemala's imports and exports of cereals, 1963-72 9 2 Guatemala's agricultural imports and exports, total imports and exports, and agricultural percentage of total, 1963-72 11 3 Average wholesale prices for beans and corn, in Guatemala City, 1972 20 ^ Average v/holesale prices for beans and corn, in Guatemala City, 1973 21 5 Average wholesale prices for beans and corn, in Guatemala City, 1974 22 6 Number of sampled farms by region and farm size. . 28 7 Number of sampled farms by region, sub-region, and department 29 8 Total inputs used in basic grain production by regions of Guatemala yk 3 Relative importance of inputs used in basic grain production by regions of Guatemala 76 10 Seed purchase and sale proportions relative to total production and total seed use 79 11 Distribution of total basic grain production by regions of Guatemala 83 12 Relative importance of the distribution of total basic grain production by regions of Guatemala . . 85 13 Marketing expenditures as a percent of average price received by enterprises and regions 91 X

PAGE 11

LIST OF TABLES--continued Table Page ]k Regression coefficients for each basic grain or association by regions of Guatemala 9^* 15 Sign and significance level of the regression coefficients for each basic grain or association by regions of Guatemala 96 16 Income elasticities of market supply for each basic grain or association by regions of Guatemala 97 17 Area elasticities of market supply for each basic grain or association by regions of Guatemala ... 99 18 Price elasticities of market supply for each basic grain or association by regions of Guatemala . . . 101 A-1 The price variable: descriptive statistics for each of the estimated equations 1 63 A-2 The education variable: descriptive statistics for each of the estimated equations 16^ A-3 The total farm size variable: descriptive statistics for each of the estimated equations I65 A-^ The distance to market variable: descriptive statistics for each of the estimated equations . . 166 A-5 The quantity demanded on the farm variable: descriptive statistics for each of the estimated equations 16? A-6 The relative profitability ratio variable: descriptive statistics for each of the estimated equations 168 A-7 The total income variable: descriptive statistics for each of the estimated equations ..... I69 A-8 R. corn-beans: simple correlation coefficients matrix of the independent variables 178 xi

PAGE 12

LIST OF TABLES--continued Table Page A-9 Rp corn-beans: simple correlation coefficients matrix of the independent variables 178 A-10 R^ corn-beans: simple correlation coefficients matrix of the independent variables 179 A-11 R^ corn-sorghum: simple correlation coefficients matrix of the independent variables 179 A-12 R^ corn-beans-sorghum: simple correlation coefficients matrix of the independent variables . , . 1 80 A-13 Rj corn: simple correlation coefficients matrix or the independent variables loO A-\h R_ corn: simple correlation coefficients matrix of the independent variables 181 A1 5 Rr corn: simple correlation coefficients matrix of the independent variables 181 A-16 R corn: simple correlation coefficients matrix of the independent variables 182 A-17 R/corn: simple correlation coefficients matrix or the independent variables 182 A-18 R, beans: simple correlation coefficients matrix of the independent variables 183 A-19 Rjbeans: simple correlation coefficients matrix or the independent variables 183 A-20 R, beans: simple correlation coefficients matrix of the independent variables 184 A-21 Ri sorghum: simple correlation coefficients matrix or the independent variables 18A A-22 R. rice: simple correlation coefficients matrix of the independent variables 185 A-23 Rjrice: simple correlation coefficients matrix of the independent variables 185 xi i

PAGE 13

LIST OF TABLES--continued Table Page A-2^ R^ rice: simple correlation coefficients matrix of the independent variables 186 A-25 R, wheat: simple correlation coefficients matrix of the independent variables 186 A-26 R^ wheat: simple correlation coefficients matrix or the independent variables I87 A-27 Regression coefficients for each basic grain or association by regions of Guatemala I88 A-28 Income-quantity relationships for the associations graphed in Figure 8 I90 A-29 Farm size-quantity relationships for the associations graphed in Figure 3 191 A-30 Price-quantity relationships for the associations graphed in Figure 10 192 A-3I Income-quantity relationships for corn graphed in Figure 11 193 A-32 Farm size-quanty relationships for corn graphed in Figure 12 19^+ A-33 Price-quantity relationships for corn graphed in Figure 13 195 A-3't Income-quantity relationships for beans graphed in Figure I'* 1 96 A-35 Income-quantity relationships for rice graphed in Figure 15 197 A-36 Farm size-quantity relationships for rice graphed in Figure 16 I98 A-37 Farm size-quantity relationships for wheat graphed in Figure 17 199 XIII

PAGE 14

LIST OF FIGURES Figure Page 1 Political divisions and transportation routes of Guatemala ^ 2 Average wholesale prices for yellow and white corn in Guatemala City, 1972-7^ 19 3 Average wholesale prices for black, white, and red beans, in Guatemala City, 1972-7^ 23 A Important crops in the different regions of Guatemala 27 5 Guatemalan small farmer consumption and selling decisions 58 6 Income-quantity or farm size-quantity relationships for the Guatemalan small farmer, given his land constraint "3 7 Hypothetical production and distribution activities for basic grains produced in the different regions of Guatemala 71 8 income-quantity relationships for the associations by regions of Guatemala 103 9 Farm size-quantity relationships for the associations by regions of Guatemala 10^ 10 Price-quantity relationships for the associations by regions of Guatemala 105 11 Income-quantity relationships for corn by regions of Guatemala 11' 12 Farm size-quantity relationships for corn by regions of Guatemala '12 13 Price-quantity relationships for corn by regions of Guatemala '13 xtv

PAGE 15

LIST OF FIGURES--continued Fi gure Page Income-quantity relationships for beans by regions of Guatemala 117 Income-quantity relationships for rice by regions of Guatemala 122 Farm size-quantity relationships for rice by regions of Guatemala 123 Farm size-quantity relationships for wheat by regions of Guatemala 127 Traditional and commercial income, farm size, and price-quantity relationships in developing agriculture 151 A-1 Mathematical properties of the specified function . 171 \k

PAGE 16

Abstract of Dissertation Presented to the Graduate Council of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE IN AGRICULTURAL DEVELOPMENT: THE CASE FOR BASIC GRAINS IN GUATEMALA By Jose Alvarez June, 1977 Chairman: Chris 0. Andrew Major Department: Food and Resource Economics A growing population with about two-thirds employed in agriculture, a limited arable land base, and poverty stricken farmers experiencing unemployment and low levels of food production are characteristics that portray Guatemala as a developing country. The nation's development efforts focus on the implementation of programs designed to alleviate those detrimental characteristics. Program objectives at the Institute of Agricultural Science and Technology ( I CTA) of Guatemala intend to develop new technologies designed to generate productivity increases especially for basic grains in the traditional farm sector. These programs will enable the country to augment supply without expanding the area committed to production. Two types of problems, however, may result from productivity advances. Small farmers could use the new technology to produce the XVI

PAGE 17

same or even a reduced quantity of grains on less land. Or, if land is fully utilized, "second generation" marketing problems are lil
PAGE 18

Total production differs among enterprises witii respect to yields and product distribution. Variations in cash sales are the result of differences in farm demand for production and consumption purposes; the more traditional the crop, the lower will be sales. The results of the regression equations support the conceptual model; in general, the estimated coefficients behave as hypothesized. Traditional crops generally appear at near zero income and farm size levels while commercial crops are cultivated when higher levels of income and farm size have been attained. Elasticities of market supply for traditional and commercial crops are high at low levels of income and farm size. However, while commercial crops still show some responsiveness at higher income and farm size levels, the traditional crop response becomes almost perfectly inelastic. This behavior is the result of farmers becoming involved in the activities of the market economy once self-sufficiency has been secured, and shifting into commercial crop production at higher levels of income and farm size. Thus, since traditional crops pervade the basic grains production system in Guatemalan agriculture, little hope prevails for the attainment of massive increases in supply of basic grains. Although corn in regions three and four and rice in regions four and five seem to have a slight potential for increased production, the resulting increases would fall far behind the goal of the Guatemalan government. XV i i I,

PAGE 19

CHAPTER I INTRODUCTION This chapter presents the problematic situation and the environment within which this research project evolved. Some of the most important agricultural and development related characteristics of Guatemala are described, followed by the problem setting and the objectives of the study. The importance of the project is discussed briefly. The data source is explained, as are the important considerations concerning use of the data in the present study. Setting of the Study Although a developing nation sharing certain characteristics with other Third World countries, Guatemala possesses unique characteristics to differentiate the country from other nations. To better understand the present study, some of Guatemala's most important physical, demographic, economic, and social characteristics are described in this section, Physical Environment Guatemala, with an area of approximately '»2,000 square miles (excluding British Honduras or Belize, which Guatemala claims as its This section is based on [2k]

PAGE 20

territory), lies entirely within the tropics. It is bordered on the north and west by Mexico, by the Pacific Ocean on the south, by El Salvador on the southeast, on the east by Honduras and the Gulf of Honduras, and on the northeast by British Honduras. The climate ranges from hot and humid in parts of the lowlands to very cold in the highlands. This wide range in climatic variation permits the cultivation of any crop grown in the Western Hemisphere. Landforms are also in great variety. The altitude varies from sea level to over 13>000 feet in the volcanic highlands. Rainfall occurs mostly from May to November and varies geographically. The Caribbean coastal plain and adjacent areas receive the heaviest annual rainfall, which may reach 200 inches. On the Pacific side annual rainfall is less and diminishes toward the coast. Guatemala City, in the highlands, averages about h5 inches of rain per year. Population Guatemala is the most populous country in Central America--4.3 million inhabitants according to the 196^ Census. The Guatemalan population growth rate, one of the highest in the world, was approximately 3.1 percent per annum at the time of the 1964 Census. It is expected that by I98O the population of Guatemala will reach 7 million people. Extremely high birth and death rates produce the consequent problems of a young population with over half under I8 years of age. The population is predominantly rural (66 percent of the population according to the 1964 Census) and is concentrated in the highlands, where the population density has greatly reduced the available land. In 1964,

PAGE 21

the population density of the country, considered among the highest in the Western Hemisphere, was 102 inhabitants per square mile. In the 1950 and 196'l censuses the population was divided into tv;o groups: Indian and non-Indian or lad i no . The first group encompasses those of pure Maya Indian descent who continue to live much as their ancestors lived several hundred years ago. The second group, in its broadest context, comprises those neither belonging to an Indian community nor wearing the traditional Indian dress and following Indian customs. Since lad i no is a cultural term, it may be possible for someone who is accepted as a lad ino in a rural environment to be classified as an Indian in the urban milieu. According to the 1950 Census nearly 72 percent of the population over seven years of age vias recorded as illiterate. This figure declined to 63 percent in the 1964 Census, with almost 79 percent of the rural and over 36 percent of the urban populations still illiterate. Although Spanish is the official language and is spoken by a majority of the population, over hO percent of the population speaks a native lanugage, with each township having its own dialect. Over 17 different Indian languages and hundreds of township dialects create special problems for the total Integration of the population within the mainstream of national 1 ife. Government and Political Subdivisions Guatemala is a Republic with three branches of government: executive, legislative, and judicial. The Republic is comprised of 22 major political subdivisions (similar to states) called Departamentos (Figure l), each Departamento being divided into a number of municipios (similar to

PAGE 22

Figure 1 . --Pol i t ical divisions and transportation routes of Guatemala Source: [2^, p. xiv].

PAGE 23

counties) of which there were 325 in ^^6^. The cabecera (capital of a municip io is called either a pueblo (village), or a villa (large village), or a ciudad (city) if it is also a Department capital. The municipio is made up of a number of aldeas (hamlets) and caserTos (small rural communities) and the cabecera of the municipio is divided into cantones (wards) The Economy Guatemala's Gross National Product (GNP) is the largest of the Central American countries, reaching 1.5 billion quetzales in 196? (one dollar is equal to one quetzal). Although growing at an average rate of 5 percent annually since 1950, the economy's growth has been erratic with substantial fluctuations in the annual growth rate of Gross National Product. Per capita income has been growing at a rate of about 2.5 percent since 1957; it changed from less than Q170 in 1955 to 03^^ in 1966. Traditional farmers' annual income is estimated at about Q85. Guatemala's economy encompasses three major sectors: domestic food production, export crops, and industry. Construction and miscellaneous services supplement the three main sectors. The Indian economy, predominantly subsistence agriculture, is largely self-supporting and regional. The Indians are not completely integrated into the money economy and sui — plus production, when present, is usually bartered or sold in local markets. Items for v/hich the Indians can not barter are purchased with money earned during the harvest season by working for wages on plantations. Domestic crop production is characterized by its low level of productivity as the result of primitive agricultural techniques and a rigid land tenure system all of v/hich sometimes require the importation of food.

PAGE 24

Much of commercial agriculture is managed by foreign firms, such as fruit companies, the lad i no aristocracy, and also by the Government. The rapid development of export products such as coffee, cotton, sugar, and beef contrasts with the stagnant characteristics of the domestic food production sector, which has been unable to develop. The industrial sector, although mainly concentrated in food processing, is rapidly expanding, having grown at an average annual rate of 10 percent between 196l and 1967This growth rate was stimulated by laws designed to grant tax benefits and by participation in the Central American Common Market. Agr icul ture Agriculture is the dominant sector of Guatemala's economy. The agricultural sector has accounted for more than 80 percent of all exports since 1953; it provides about 30 percent of all raw materials used by domestic industries; and the sector employs about two-thirds of the population. Agriculture also accounts for about one-third of GNP. Major crops are corn, rice, wheat and beans and three major export crops — coffee, cotton, and bananas. Minor export crops include essentia' oils, tobacco, and honey. Crops primarily for domestic use include rubber, cacao, fruits and vegetables, sorghum, millet, sesame, potatoes, cassava, and hard fibers. Livestock and poultry are also important and have grown rapidly in the last decade. Agricultural activities take place within a very rigid system of land tenure. Over 98 percent of the farms have an area under 100 acres

PAGE 25

and occupy 28 percent of the land being farmed. On the other hand, only 0.1 percent of the total number of farms are larger than 5,000 acres, but they occupy Al percent of the farm land. In the 1950 Census, 1.3 million people 1 ived on landholdlngs averaging 3-5 acres, the minimum amount considered sufficient to satisfy the basic needs of one family. In 1965, the situation was even worse; the Guatemalan National Planning Council estimated that the number of landless families had increased by l40,000 and that over 90 percent of all rural families were either landless or possessed insufficient land for subs istence. Markets and Marketing Markets and fairs occupy a very important place in the life of rural Guatemala. Each community holds at least one special market day per week, which is a socio-economic institution. Although these markets are the traditional response to the economic conditions of Indian life, pricing is determined not by customs but by supply and demand conditions. Sellers are mainly Indian women; buyers are both Indians and ladinos . Products, ranging from food to handicrafts . and clothing, are displayed by type and origin. Each township is known for a particular commodity being less expensive than in other markets. They may continue for several days and attract people from all over the country. Besides markets and fairs, marketing activities in the countryside take place in small general or neighborhood stores. These stores are often located in the onwer's home. In larger towns, stores are of a permanent structure and owners are professional merchants.

PAGE 26

8 Guatemala City, the capital, possesses a large number of retail stores, one large plaza market for each of 15 zones, a central market, and a number of wel 1 -stocked supermarkets. The capital is also the principal marketing and distribution center for all imports. Marketing activities are severely handicapped by the bad quality or lack of communication. Certain regions of the country still remain relatively isolated (Figure l). Much of the produce for domestic trade is carried to the local market on the backs of men and mules over dirt trails and footpaths. Foreign Trade Guatemala's foreign trade is characterized by a large number of trading partners, a short list of commodities traded and for most years an unfavorable balance of trade. Guatemala maintains commercial relations with about 76 countries and is signatory to several international agreements. The United States is Guatemala's primary trading partner, although this share has been slowly decreasing. Coffee, cotton, sugar, beef, and bananas are the main exports. Nickel and flowers are new promising export products. Consumption goods are the primary imports. in each year between 1957 and I969, with the exception of 1966, Guatemala experienced unfavorable trade balances which had to be financed by credits and loans. Agricultural products are the most important items of foreign trade. Very low levels of grain production in Guatemala have forced the importation of cereals and the consequent annual deficit in cereal trade (Table 1). From I963 to 1972, agricultural imports represented 13-^ to

PAGE 27

Tabic 1 .--Guatemala ' s imports and exports of cereals, 1963~72 Year 1963 196^ 1965 1966 1967 1968 1969 1970 1971 1972 Imports Exports Millions of U.S. Dollars 7.6 8.0 7.8 7-0 8.6 8.7 7.0 10.2 9.9 10.8 0.1 0.2 0.6 0.8 1.0 1.1 1.2 1.8 1.3 2.5 Deficit 7.5 7.8 7.2 6.2 7.6 7.6 5.8 8.^ 8.6 8.3 Source: [117, P8^^].

PAGE 28

10 9.2 percent of total imports. Agricultural exports, on the other hand, have represented between 69 and 88 percent of total exports during the same time period (Table 2). For both imports and exports, agriculture's share of trade had declined. Yet it is important to note the extremely important role played by the agricultural sector's export surplus in the overall trade balance situation for Guatemala. Over the 1963-72 period this role increased as the share of agricultural imports of total agricultural trade declined from about 14 percent to 11 percent. Setting of the Problem Introduction The above description portrays Guatemala as a developing country. Most of the character isti cs descri bed are common in other Third World countries. First, the country's population, especially the rural population, is growing rapidly. The Guatemalan population growth rate at approximately 3-1 percent per annum is high. When the population of Guatemala reaches a projected seven million people in I98O, 63 percent of the economically active population will be employed in the agricultural sector. Compared with 65 percent in 1964, this represents an insignificant decrease. Although employing 65 percent of the labor force, agriculture only contributes about 30 percent to the Gross National Product [35]. Another characteristic common to Third World countries is that Guatemala has a limited arable land base. Yet a large percentage of privately owned land is idle as a result of the prevailing land tenure

PAGE 29

11 Table 2 .--Guatemala ' s agricultural imports and exports, total imports and exports, and agricultural percentage of total, 1963"72

PAGE 30

12 system [2h, p. 260j. Nearly all arable land in the highlands is presently under production. Government policies prohibiting tree removal to bring new land into production in regions such as El Peten contribute to a land scarcity condition that is further aggravated by the population situation. A third characteristic, common to other Third World countries, is that many Guatemalan farmers live in poverty conditions, are often unemployed and unemployable, and have very low levels of food production. For example, net income per capita in the central highland region has been estimated recently to be Q117 per annum [26, p. k3] • In the sam.e area, real product per capita went from Q77 in 1951 to Q51 in 19^6 [35, p. 23]. A recent study conducted by the Institute of Agricultural Science and Technology (ICTA) in the community of Santo Domingo Xenacoj supports these figures [17]. The community, where family income averages from Q90 to Q200 per year, is plagued by such a high unemployment rate that part of its population is forced to migrate to cities and the coast in search of new employment opportunities. Successful efforts directed to solving population, employment, land use, and income problems will benefit Guatemalan development. The implementation of programs leading to more intensive land use, the reduction of unemployment, and the increase in production and productivity in rural areas ought to receive top priority among the country's development efforts. Agriculture, especially small farm agriculture, can play an important role in Guatemala's march towards economic and social development. In 1951 a mission sponsored by the International Bank for Reconstruction and

PAGE 31

13 Development reported that "it is clear that any appreciable rise in Guatemala's standard of living can come only through improvements in agriculture" [51, p. 27]. Several researchers have suggested that programs to improve agriculture should be oriented toward small rather than large farmers because small farmers utilize scarce resources more efficiently in food production [19, 35, ^7]. Furthermore, the contribution of the traditional small farmer to overall production, especially basic grains production, is relatively large. Fifty-five percent of total basic grains production in the country comes from farms under seven hectares. Waugh states that it is evident that the small farmer's production is of first order of importance to the country. He goes on to say that this production results from a very limited percentage of the land in farms and that 67 percent of the total number of farms in the size group 1.7 to 7 hectares have only 18 percent of the total land in farms [118, p. 2]. Furthermore, it is in the small farm sector where economic and social development are most needed. Certain characteristics of Guatemalan agriculture necessitate program formulation at the subsector level. Fletcher £t_a_L«[35, pp. 51, 53] identified three subsectors in Guatemalan agriculture: the traditional agriculture of the highlands (corn, beans, wheat) and other parts of the country; export crops (coffee, cotton, and bananas); and commercial agriculture mainly for domestic consumption (the majority of the remaining crops). Since these subsectors face different produce demand schedules and marketing problems, agricultural development programs will be most successful when formulated at the subsectoral level. Accurate problem identification leading to specific solutions for each subsector would

PAGE 32

14 then be easier. This study is mainly concerned with the traditional (subsistence) and commercial subsectors of Guatemalan agriculture. A distinction ought to be made between traditional and commercial farmers, 2 and between traditional and commercial crops. The term traditional farmer does not necessarily include only Indian pre-Colomb ian types of agriculture; It is also used to signal farmers who historically ignore market stimuli and are not prepared to shift from one crop to another; they can not respond easily (neither economically, culturally, nor technologically) to stimuli. In general, the term traditional means any system which has been used for "a long time" and has not been "modernized" particularly in the use of petroleum based products. Although these farmers may use some fertilizer in some regions (where water is available), they apply almost no insecticides (ownership of a sprayer means an additional investment). The commercial farmer is price responsive and has the means to shift between crops; his farming is a business and he responds to market stimuli. The difference between traditional and commercial crops is based on the destination of the product and the utilization of labor in its production. In traditional crops, farmers tend to use about 80 percent family labor and 20 percent contract or hired labor, and, although some output may be sold when a surplus occurs, production is mainly devoted to family consumption. In commercial crops the characteristics are 2 The discussion is based on personal communication with Peter E, Hildebrand, Coordinator, Socioeconomics Program, I CTA-Guatema la .

PAGE 33

15 almost exactly the reverse. These sharp distinctions among subsectors validate the assertion concerning the necessity of formulating programs at the subsectoral level. Work at the Institute of Agricultural Science and Technology ( I CTA) of Guatemala is focused on subsectoral problems. On January 20, 1976, the Minister of Agriculture of Guatemala announced that the government was launching a program to increase agricultural production with special emphasis on basic grains [22, p. 1]. Accordingly, iCTA's 1976 plan comprises production programs for different agricultural products (corn, beans, rice, wheat, sorghum, vegetables, and hogs) with the support of disciplines such as Soil Management and Rural Socioeconomics. The creation of the Program of Rural Socioeconomics is the result of ICTA's pol icy based ... in the belief that an appropriate technology can only be developed through the study of the causes conditioning the application of new technologies and this is achieved by means of agro-socioeconomic studies at the farm level in continuous contact with the farmer vjho will be its principal usufructuary . Therefore, the contribution of the social sciences (Economics, Sociology, Anthropology), is the key which will enable us to know these causes and will permit the recommendations to be based on the agronomic research and correspond to the requirements of the environment to which they are intended. .. [53 , p. 217]Problem Statement ICTA's subsectoral programs are intended to develop a new technology based on the environment in which farmers live, to generate productivity increase that make it possible for Guatemala to supply its growing population with more agricultural products per capita without an increase in the area used in production. For example.

PAGE 34

16 several diseases and weeds affecting corn have been controlled and, by utilizing a new seed variety, yield per acre in La Maquina, located in the Such! tepequez Department, can be doubled and even trebled. Another example pertains to research on interplant ing beans with corn and on insecticides and new seed varieties that will eventually lead to larger bean yields. Research on wheat is seeking new seed varities with high productivity and resistance to primary diseases and adapted to different regions of the country and small farmer use. The new wheat variety, "Gloria", introduced in the Cooperative Santa LucTa, R.L., hcs' doubled wheat production and has been accepted by the farmers of the area [52]. Since the new technology is being developed considering the conditions and limitations that farmers face, farmers are making full and best use of the technology. The adoption of the new technology, it is hoped, will foment increases in production and productivity. In Guatemala, as in most developing countries, a large portion of agricultural production is consumed on the farm. Thus, the adoption of new production techniques may arise from the desire to sell the extra production for cash. Very little is known, however, about the intensity of marketing and consumption problems that must be faced if farmers market most of the increase in output. An increase in marketed output may intensify the strong tendency towards price instability inherent in the marketing of agricultural products. Abbott attributes instability to the seasonal concentration of output, great difficulties in adjusting production closely to demand

PAGE 35

17 in view of the uncertainties of weather and yields, and to the relatively low price elasticities of demand for the basic food products [2, p. 6]. Productivity advances can also show how rapidly the so called "second generation marketing problems" can arise. Falcon, when writing about the Green Revolution, expressed his hope that decision makers in the future will heed the warnings earlier of marketing specialists and will react before critical product distribution situations develop [32]. Such problems range from the early identifiable problems related to drying, storing, transportation, etc., to the less identifiable, but not less important, problems of pricing and markets. It is extremely important to face these problems on a timely basis, avoiding the erroneous belief that marketing is an accomodating, spontaneously generated activity that can be somehow performed once production has been increased. The following research is addressed to more fully understanding the differences in supply response in the traditional and commercial subsectors due to changes in agricultural technology. Market problems in the future will combine with those at present such as unstable agricultural prices, the absence of adequate marketing channels for both inputs and outputs, and the lack of knowledge concerning demand and supply relationships. The vast importance of corn to the national economy and, in particular, to small farmers in the highlands has been documented [98], yet it is surprising how little information related to corn marketing is available. For example, there are no complete and reliable data for corn moving through the different marketing

PAGE 36

18 channels. The lack of drying and storing facilities causes concern to government officials, wholesalers, and farmers. Surveys conducted by the Agricultural Marketing Board reveal substantial differences in losses during marketing among the different zones of production due to differences in storage, transportation and processing. Fletcher, et al say that the majority of the important problems prevailing in corn marketing are related to the lack of adequate facilities for drying and storing [35, p. ^3], which causes substantial losses and produces considerable variation in the price of corn (Figure 2 and Table 3 to Table 5). The variability in the price of corn may benefit those who can store large amounts of corn for three to six months, but neither helps the small farmer who needs cash at the time of harvest nor the consumer who buys this product in small quantities. The same phenomenon prevails in bean marketing (Figure 3 and Table 3 to Table 5). Price stabilization for corn and beans, therefore, is an important objective of the Guatemalan government. The need for conducting supply and demand studies in the rural areas is evident. An important aspect on the demand side is the quantity of basic grains that small farmers demand. Since much of their production is consumed on the farm, knowledge of their demand is needed to estimate the future amounts of basic grains they will send to the market as a result of increased production. Since the nature of the available data does not permit the identification of demand functions, this research will be focused mainly on supply.

PAGE 37

19 3 O 0) en < -30^ I I I . I -hW -3I CM o to E (D *-> D C3 C s_ o o

PAGE 38

20 Table 3---Average wholesale prices for beans and corn, in Guatemala City, 1972 Month

PAGE 39

21 Table A. --Average wholesale prices for beans and corn, in Guatemala City, 1973 Month

PAGE 40

22 Table 5-~~Average wholesale prices for beans and corn, in Guatemala City, 197^ Month

PAGE 41

23 < H 1 1 1H H \ K -f-\V re E 0) 4-1 (U t3

PAGE 42

2h On the supply side, detailed market knowledge and research on where, when and for what price products can be sold is essential in determining what to produce. Due to very large seasonal and cyclic fluctuations in the prices of agricultural products, farmers in developing countries rationally choose to grow sufficient food for home consumption. Market supply functions are important in determining how responsive farmers are to price, income and other variables for policy decisions aimed at securing adequate increases in the marketed supply of food crops. Since the responsiveness will be different in different milieus, elasticities of supply must be estimated separately for different regions. Market supply functions may also signal possible future changes in land utilization. It has been observed very recently in the communities of San Martin Jilotepeque and El Novillero that, as the small farmer obtains a better standard of living resulting from new corn technologies, there is a tendency to reduce the amount of land devoted to corn production since this is mainly cultivated for family consumption [107]. Knowledge of the characteristics of production and distribution activities is needed. Their description and quantification, especially in the market for inputs, will show cost and availability of inputs in each region. Comparing results with actual output in the region may provide a basis for identification of problems that can be solved by policy decisions. In a marketing study of basic grains, the Institute of Agricultural Marketing (INDECA) delineated the marketing channels for these products [S^] The study lacks, however, the corresponding

PAGE 43

25 data for each channel and therefore it is impossible to know the relative importance of each channel; it also contains no information about the movement of inputs to small farmers. There is no doubt that the existing problems and those that will be generated by the increase in production and productivity of basic grains require careful study to avoid the imminent "Green Revolution" second generation problems. Knowledge of total supply and marketed supply functions, production and distribution activities, and the behavior of the surplus-output ratio as income and farm size change, is important in solving present problems and in trying to avoid major market problems in the future. It is in this context that the follov/ing objectives are undertaken. Objectives of the Study The objectives of the study are to: 1. Estimate market supply functions for basic grains in the different regions of the country and compute the corresponding income, farm size, and price elasticities of market supply. 2. Delineate and quantify input acquisition and product disposition for basic grains in the different regions of the country. Data Source and Data Considerations The data are derived from the Small Farmer Credit Survey conducted by the Government of Guatemala and the Agency for International Development (aid) in 197^ for agricultural activities during the 1973 calendar

PAGE 44

26 year. These cross section survey data contain necessary and valuable information for conducting this research since time series data are completely unavailable. The overall objective of the survey was to compare the performance of small farmers receiving credit from the government with non-recipients. A sample was selected by sub-region in order to have a minimum number of sample farms producing the designated main crop for each sub-region. Interviews were taken with 800 pairs of farms, from which a total of 1,5^8 questionnaires were completed. Figure k shows the different regions with their respective important crops. Table 6 and Table 7 present the number of sampled farms and farm size by region, sub-region and department, respectively. By reviewing Figure 1, it becomes evident that the survey reached every Department in the nation, except El Peten (Region two) which is a semiisolated area in the process of colonization. A word of caution about the representativeness of the data is appropriate. The no-credit farmers were selected because of their similarity in age, size of farm, crops grown, etc., to the group of farmers receiving credit. Therefore, the former group would represent all farms in Guatemala only to the extent that the latter group does. Interest however falls in drawing conclusions about traditional and commercial agriculture at the regional level. In this case the sample does contain enough farms engaged in either or both types of agriculture such that conclusions by farm type at the regional and national levels are possible. Complete descriptions of the sampling procedures are available in [19, 106]. More information about the survey's results is contained in [75, 92, 101].

PAGE 45

27

PAGE 46

28 Table 6. — Number of sampled farms by region and farm size

PAGE 47

29 Table 7.~~Number of sampled farms by region, sub-region, and department Region Sub-Region Department No. Department Name No. of Observations 1 2 2 3 3 3 3 k k 5 5 5 6 7 6 6 7 8 8 8 9 9 9 10 10 10 11 11 12 12 13 15 15 16 13

PAGE 48

30 George and King's arguments in support of the use of cross-section data in tiieir research [37] can be extended to the present study. First, time-series data are not available; but even if they were, more reliable (demand) parameters can be estimated with cross-section data. In static analysis, a (demand) relationship is specified for a particular period of time. In practice, as George and King point out, [37, pp. 28-9] each time an observation is made, we get one point on a (demand) curve and, by the time another observation is made, the curve might have shifted because one or more factors influencing (demand) may have changed. These shifts may influence the nature of functions obtained from timeseries analysis and, at times, it will be difficult to isolate the effects of such shift variables from purely economic variables such as prices and income. Thus, wrong conclusions about the non-significance of economic variables in explaining (demand) could be drawn. Second, since prices generally remain unchanged during a short period of time, cross-section data make it possible to estimate income elasticities free from price effects. George and King state that crosssection data primarily reflect the (demand) pattern in the sense of long-run income changes so that the income elasticities computed from these data can be interpreted as long-run elasticities. From the point of view of practical applications of (demand) analysis, these long-term elasticities are more relevant for many policy decisions than the shortterm elasticities obtained from time-series data.

PAGE 49

31 Relevance of the Project Income and farm size elasticities of market supply are important determinants in signaling farmer behavior concerning potential increases in quantities produced and marketed and in land utilization. These elasticities permit the estimation of the effects that may result from future increases in productivity and production, if in fact they occur, and in income. Price elasticity may also be computed but would be less meaningful due to the nature of the data. Price observations from the crosssection data available do not capture seasonal prices because interviews were taken at one time due to research resource constraints. The aggregate prices taken can create price elasticity situations without easy interpretation and application. This drawback, however, appears to be less relevant as emphasis is given to the income and farm size elasticities and the income-quantity and farm size-quantity relationships as indicators of farmer supply responsiveness to factors that change his income and farm size. One of the most important implications of testing the theory presented in this study is obtaining a better understanding of the basic economic system of small farmers and the relationships between this system and Green Revolution agriculture. The theory suggests that there is a built-in supply control mechanism for basic grains and low valuelow risk crops in the small farm system. This mechanism, explaining why productivity increases yet production is stagnant, is a natural reaction to basic subsistence needs and avoids some of the second and third generation problems of the Green Revolution [32]. Overproduction may not

PAGE 50

32 usually result so prices would not decline sharply to create great income disparities and the usually disoriented market system itself would not be so forcefully challenged. Should these hypotheses prove reasonably accurate, research and development programs might carefully consider the total small farm system. Basic research on basic grains alone will not serve the small farmer's developing needs entirely as he moves into higher value-higher risk crops. Meeting the risk element squarely in both agronomic and economic research programs might be most productive. Organization of the Dissertation The setting of the study, with its problematic situation and implications, has been presented in this chapter. The theoretical framework of the second chapter describes the role of agriculture and of marketing in economic development, with special emphasis on the theory of demand and supply in LDCs. After the theory and literature are reviewed, the methodology used in accomplishing the objectives is presented in the third chapter. The fourth chapter describes input acquisition and product disposition for basic grains in the different regions. Chapter five encompasses both the results and the corresponding analysis, and the sixth chapter contains a summary, the conclusions, and recommendations based on the results obtained. The final chapter, "Reflections on the Theory of Development," is an attempt at actualizing the current development literature of the second chapter in light of the findings in chapter five.

PAGE 51

CHAPTER I I AN EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT That part of the development literature related to agricultural development and marketing is summarized in this chapter. The relationships between agriculture and economic development are the subject matter of the first section. The second section describes marketing activities and their role in the development process with special emphasis on the theory of demand and supply in developing countries. Agriculture and Economic Development Since World War II the literature has paid increasing attention to the process of economic development in the developing countries. There seems to be a consensus on the need for sustained growth to bridge the gap that separates LDCs from the industrialized nations. Though the problem of an overall development strategy is continually discussed, the key role that the agricultural sector has to play is today widely accepted. In this chapter, some of the most important viewpoints, especially those related to the problematic situation described above, are analyzed. 33

PAGE 52

3A Agriculture in LDCs: A Changing Spectrum of Priorities Arthur Gaitskell [3^, pp. ^6-50] has tried to explain why agriculture until recently has experienced a very low priority in developing countries. He enumerates the following reasons: (a) Since the richest countries in the world are the industrial countries, it seemed logical that industry, rather than agriculture, was the means for development. (b) Developing countries have been sources of raw materials for the industrialized nations and a market for their manufactured products, but their terms of trade have been deteriorating. Developing their own industries, therefore, seemed to be a correct goal. (c) Private foreign investment was, for a long time, the pattern of development v/ithout any national participation. (d) Traditional values ("not everybody gives development top priority in their lives"): Leisure, status, religious precepts, traditional methods of ancestors, etc., played an important role in hampering agricul tural development. (e) Decision makers in LDCs come from the educated-elite and they are fundamentally urban oriented. (f) Other reasons favoring industrialization were: it has a greater appeal than agriculture to LDCs since it suggests the modern world. Machinery can be imported; it is easy to learn how to use it and see the results. Agriculture on the other hand is old and most people think they already know all about it. Industrial output is less

PAGE 53

35 uncertain than crops. Since a minority is engaged in agriculture in the industrial countries, industry seemed the obvious target for which to aim. Finally, since in the most developed countries, industry's surpluses have been used to pay for subsidies, a cause for technological success, the idea of developing industry first found greater appeal . There has been, however, a recent shift to complementary growth of agriculture and industry. Gaitskell [36, pp. 50-6] attributes the attention given to agriculture to several facts: (a) The existence of undernourishment and poverty is today a main purpose for encouraging development. Since the main areas affected are the rural areas, it follows that agriculture has to be developed. (b) The "left-outs" from rural areas constitute a serious threat to existing political regimes. (c) Industrialization alone can not solve the unemployment problem since it is capital intensive. (d) Foreign exchange earnings from agriculture are necessary to buy the basic imports needed for industrialization. (e) The increasing need for food as population increases and land becomes even more scarce. The time has come for proper priority to be given to progress of the agricultural sector in developing countries where resources are favorable and population growth is pressing.

PAGE 54

36 Agriculture versus Industry: A False Issue The issue of establishing development priorities in LDCs is of utmost importance. In the process of making a choice, economists have embraced one of two opposing views: those recognizing that top priority should be given to increase food supply, and those advocating a "big push" industrialization program. Among the advocates for the first group are A.E. Kahn, J. Viner, Coale and Hoover, and others, while A.Hirschman, Liebenstein and Higgins, among others, belong in the second group. Heady [46, pp. 66-7], though recognizing that there is no univeral rule for making a choice between the two, outlines several cases in which a choice can be appropriately made in either direction according to specific circumstances. Nicholls [89, p. 16] believes that the choice is a matter of degree and not of kind, and states that there is probably no developing country in which it is feasible to concentrate all of its investment on either agriculture or industrial development, and it will be impossible to concentrate on industry until a reliable food surplus has been achieved and sustained. Since in most LDCs there is still a large agricultural majority coupled with large rates of population increase, Dovring [27, p. 95] wonders how large the rate of industr izal ization must be to absorb the annual increments in the labor force and reduce the existing surplus in agricul ture . Meier's comments on the issue seem to summarize very well the current status of the debate: The attainment of a proper balance between the establishment of industries and the expansion of agriculture is a persistently troublesome problem for developing nations. In

PAGE 55

37 earlier discussions of development priorities, deliberate and rapid industrialization was often advocated. Experience, however, has shown the limitations of an overemphasis on industrialization, and it is increasingly recognized that agricultural progress is a strategic element in the development process. Industrial development versus agriculture has become a false issue, and the concern now is rather with the interrelationships between industry and agriculture and the contribution that each can make to the other. It has also become apparent that the relative emphasis to be given to industry and agriculture must vary according to the country and its phase of development [80 , p. 285]. The Role of Agriculture in Economic Development Papanek [93, PP289-91] advances several economic arguments for heavy emphasis on development of the agricultural sector. The arguments apply to the commercial and large scale (capital intensive) farms. First, it is necessary to free labor for industrial development. Second, agricultural production can be raised rapidly and with little capital (possibility of doubling crop production, or raising crops in previously uncultivated areas, fertilizer use, improved seeds, etc.), while industrialization requires time and capital, skilled workers, managers, social overhead capital and the like. Third, while the development of the agricultural sector is capital-saving in requiring minimum expenditures for overhead costs by obviating massive population movements, industrialization would require heavy expenditures to provide at least minimal facilities to the new city inhabitants. Fourth, development of agricultural production also is often the fastest method for decreasing needed imports or increasing saleable exports in countries needing and lacking foreign resources. Fifth, structural changes may be needed before technical improvements in agriculture can be carried out without prior

PAGE 56

38 industrialization. Finally, increased incomes will produce increased demand for food and clothing. Agricultural production or imports v;i 1 1 have to be increased as part of the development process since reinvestment of all of the increased production can not be expected. The five propositions stated by Johnston and Mel lor [58, pp. 2917] about the ways in which agricultural development, especially large scale agriculture, contributes to over-all economic development follow directly from the former arguments. First, economic development is characterized by a substantial increase in the demand for agricultural products, and failure to increase food production in pace with the increase in demand can serious 1 y impede ovei — all economic development. Second, agricultural exports may provide foreign exchange earnings. Third, the labor force for the expansion of the industrial sector can contribute the capital required for overhead investment and expansion of secondary industry. And, finally, rising net cash incomes of the rural population may be important as a stimulus to industrial expansion. There is no longer any doubt, according to Schultz [108, p. 5], whether agriculture can provide a tremendous stimulus for over-all economic development. It is only necessary to invest in agriculture and, above all, to provide farmers with incentives. Once there are investment opportunities and efficient incentives, as he puts it,^ farmers will turn sand into gold. The role of agriculture in economic development according to Nicholls [89, pp. 11-3] depends heavily upon the particular historical circumstances of the country and upon the ratio of agricultural land to population. The relative emphasis which decision makers give to

PAGE 57

39 agriculture, and the consequent policies must therefore vary accordingly, But it is clear for him that, either for an open or closed economy, the agricultural sector can make tremendous contributions to over-all economic development and that, within considerable limits at least, the development of this sector is a sine qua non before a take-off into self-sustained economic growth can become a reality. In many countries, however, agriculture has failed to respond for what Heady [46, pp. 63-h] calls obvious reasons. First, agriculture has not been given an appropriate priority. Second, there is a lack of a price structure conducive to the use of new and more capital resources such as insecticides, fertilizers, and improved seed varieties. Third, input prices have been kept too high and output prices have been kept too low. Fourth, capital has not been moved into the hands of subsistence farmers to incorporate them into the market economy. Fifth, frequently, the absolute supply of and the facilities to move and store inputs are lacking. To eliminate those adverse factors, several economists have suggested different prescriptions. Some Prescriptions for Agricultural Development Many sophisticated models have been provided for developing the agricultural sector in LDCs. Except for Heady and Lewis, all of the authors call for increasing employment on farms rather than replacing labor with mechanized technology. For Heady [kS, p. 61 ] there is no mystery in the process of explaining the development of agriculture. It is so simple that no new theory is required. He proposes the following "recipe":

PAGE 58

ho Lower prices and increase availability of resources, add certainty and greater quantity to product prices, blend with knowledge and a firm or tenure structure which relates input productivities appropriately with resource/product price ratios. This mixture can be brought to a developmental boil in a container of commercial farming, if not successfully in a purely subsistence environment which is outside the market economy. It will have a delayed or lagged maturity, depending upon the dosage of the above variables and the extent to which a very few specific cultural factors exist. These factors include (1) creating a new "state of mind" for cultivators who have previously been oriented to production best guaranteeing food for subsistence in the year ahead, and who must now look to expansion towards the market, and (2) acquainting families with the mysteries of managing credit and capital in order to convert them from subsistence operations. This recipe has been tested and proven successful over many parts of the world: so much that it Is doubtful that anyone will ever come up with a better one. Hence, the creation of the conditions implied above is one of the priorities for bringing economic development to agriculture. There is no mystery to the process. If a mystery exists. It Is to explain those exogenous conditions which prevent governments and planning agencies, which wish agricultural development, from manipulating the above instruments and going forward with the recipe [kS , p. 63]. Lewis' well-known article on "Economic Development with Unlimited Supplies of Labour" [7^] deserves special consideration. According to him, in most developing countries the supply of labor is perfectly elastic at current wage rates. The existence of disguised unemployment in the agricultural sector, with zero or even negative marginal productivity, provides the basis for economic development. As workers are absorbed by the industrial sector, capitalists earn a surplus, the surplus can be Invested with the resulting increase In marginal productivity and, therefore, growth. Despite the controversy that followed publication of this position, the article exerted tremendous influence in the 1950's and 1960's.

PAGE 59

Premature displacement of labor from agriculture, however, could hamper economic development. The demand for food (determined largely by population growth and by the income elasticity of demand for food) and the existing high rates of population growth with the difficulty experienced by the urban sector to absorb this growth, yields the Johnston and Mel lor policy prescription of ...a labor-intensive approach with reliance on yield-increasing technical innovations in the earlier phases of agricultural development. This policy approach produces the required increases in agricultural production and avoids displacing labor prematurely from agriculture. It is a prescription for agricultural research, for large increases in the use of yieldincreas ing inputs such as fertilizer, improved seeds, insecticides and pesticides, for increases in irrigation facilities and for building service institutions in extension, marketing, and credit. It is also a prescription to minimize mechanization, especially when it serves to displace labor [26, p. ^5]. Dorner [25, pp. 268-72] also points out important areas in which policy changes could strengthen economic development and the status of the small farm subsector. Of special interest to our case are: First, development and introduction of new technology to increase employment and production, with special emphasis on land saving technologies if both increased production and employment objectives are to be served. Second, modification of rural service structure to assure access by small farmers. No matter the prescription followed, it is essential to remember, as Hirschman states, that "... development depends not so much on finding optimal combinations for given resources and factors of production as on calling forth and enlisting for development purposes resources and abilities that are hidden, scattered, or badly utilized"

PAGE 60

k2 [^S, p. 5]. And that "there are always and everywhere potential surpluses available. What counts is the institutional means for bringing them to life... for calling forth the special effort, setting aside the extra amount, devising the surplus" [95, P339]. Marketing and Economic Development A negative feature of pricing systems in developing countries is the existence of extremely high prices at the retail level restricting consumption along with extremely low prices at the producers' level which do not stimulate farmers to grow and market more products. There exists no doubt that inefficiency in the marketing of agricultural products is characteristic of most developing countries. Despite the importance of well organized and efficient distribution systems, the study of the role of marketing in LDCs began only two decades ago. The purpose of this section is to profile the important role that marketing plays in economic development. Marketing Defined Marketing may be defined in several ways. In a broad sense, marketing can be identified as "part of the production process that assures market outlets for farm products and makes readily available supplies of production inputs which reduce price uncertainty and risk" [115, P!]• ^Abbott [2, p. 36'*] affirms that the first to point out specifically the importance of marketing in economic development was R.H. Holton in the beginning of the 1950's.

PAGE 61

43 In a conference about marketing problems in LDCs [66, p. 6], agricultural marketing is considered to consist of four specialized areas or activities. The first area, "factor marketing", encompasses the functions of providing inputs for farming. The second is the movement of commodities to consumers. The third area is concerned with the activities performed by the processor converting the commodities into products. The fourth is related to the export of the commodity. Marketing operates in a certain environment and is affected by different forces. Technology is, in our case, the most important factor to consider. "Technology puts pressure on a marketing system to which it must adjust, and similarly, technology has much to do with the products distributed and their eventual acceptance" [^9, P2]. Reynolds [100, p. 15^] says that marketing is affected by technological change in three ways: by change in goods and production methods, by changes in the ultimate consumer, and by changes in marketing itself. The Role of Marketing in the Economy An AID publication [67, pp. 27-8] lists three broad functions that the marketing system performs in the economy. First, it performs the reciprocal function of providing an outlet for producers and commodities for consumers (household and processing firms). Second, it provides a livelihood for those performing the different marketing activities, and should yield reasonable returns to the capital and managerial abilities devoted therein. Third, it signals those engaged in the production, distribution, and consumption of commodities the actions they should take in their own interest.

PAGE 62

kk The importance of marketing can be appreciated in the triple functions enumerated by Drucker [28, p. 335]: the function of crystallizing and directing demand for maximum productive effectiveness and efficiency; the function of guiding production purposefully toward maximum consumer satisfaction and consumer value; and the function of discrimination, rewarding to those who really contribute excellence, and penalizing those who do not want to contribute or to risk. The economic aspects of marketing, according to Holloway and Hancock [^3, p. 1], are twofold in importance: First, consumer's behavior is influenced by their economic status which creates an environment for other influences to act upon the consumer. Second, firms act in the market in a competitive atmosphere with price serving as a signal to exchange transactions. "In this way the economic dimension is broadened, and the economic environment of the firm becomes a market force worthy of consideration" [k3, p. 1]. The Role of Marketing in Economic Development Marketing is an essential consideration when planning economic development. Moyer and Hollander [Sk , p. 2] attribute the importance of marketing in that process to the fact that it permits increased agricultural output to be moved into commercial markets, and since distribution systems link markets with markets and producers with markets, these systems equalize and distribute goods from surplus to deficit areas. Since producers and consumers are separated geographically, production and consumption cycles are different, food products though harvested

PAGE 63

A5 intermittently are consumed at fairly regular intervals, and the necessity of marketing agents is evident to keep goods flowing both geographically and through time. The economic development process will suffer if this distributive function is not well performed. King [Sk , pp. 78-9], in analyzing the importance of marketing in economic development, states that it is desirable that farmers respond to prices and income incentives for three goals: a nutritional goal, a price stability goal, and a growth goal. Inefficiencies in the production of marketing services and in the pricing system interfere with the achievement of such goals. Three basic conditions, according to Abbott [3, p5], are of special importance in assisting market demand to provide production incentives: reasonably stable prices for agricultural products at a remunerative level, adequate marketing facilities, and a satisfactory system of land tenure. Despite its apparent importance in economic development, late • emphasis on marketing may be due to the centuries-old belief in the unproductive nature of marketing and middlemen or possibly to the belief that marketing is an accomodating mechanism and that firms will appear to provide the necessary services once the need for such services has been felt. Collins and Hoi ton [16, p. 36O] have demonstrated the erroneous nature of the latter point. They emphasize the need for special attention in transforming the organization and operation of the distributive sector rather than the physical facilities. Abbott [1, pp. 87-8] attributes the neglect of marketing in development plans to two possible causes. One is the belief that a laisez f a i re attitude will better solve problems than if solutions are

PAGE 64

^6 included In a plan. The other possibly Is the ignorance of planners about the importance of marketing or their lack of interest in the subject. Going to the other extreme, there may exist the temptation of giving marketing an over emphasis and vyithout sufficient attention to production. Heady and Mayer [^5, p. 31] have already given warnings about this tendency when they state that both the producing and the marketing sectors should be considered and tackled together. Two opposite examples of imbalance are: (l) the case when increased food production is penalized in the market and the production potential is not realized because consumer preference places a low value on the commodity; and (2) the situation when large investments of effort and funds are made in marketing research and facilities without relating these investments properly to production conditions. Times and attitudes about marketing and development are changing as stated by one author who wri tes. . ."countering the crude notion of the non-productivity of marketing is the growing realization that the activities performed in transforming farm products in space, form, and time are a useful and necessary part of the economy" [3^, P132]. This growing consensus conveys the idea that changes are needed not only in the distributive sector to help the development process, but that this sector can actually play a leading role in that process. Collins and Holton [16, p. 3^0], in arguing against a passive role for marketing, state that the distributive sector can under certain circumstances play a very active role by changing demand and cost functions in such a way as to encourage the expansion of the agricultural and manufacturing sectors. Rising productivity, according to

PAGE 65

47 Fletcher [3^, p. 132], creates demand for services produced by different marketing firms and the strategic position of the distributive sector gives it a leading role in development. He further argues that in LDCs there is a need for a relatively heavy emphasis on technological efficiency as contrasted to economic efficiency (consumer satisfaction is more important than consumer sovereignty) and that the marketing system is the necessary connecting link between consumers and an Increasing volume of food and fiber production. There are many variables influencing the distributive sector in LDCs. An important publication [67, p. 5] lists the following: the stage of technology In its agricultural production system and in its overall economy (the rate of agricultural growth); how well the country's domestic production can meet the country's food needs (the extent of the dependence on external food aid) and the extent to which a few crops make up the bulk of the people's food supply; the extent of urbanization; the level and distribution of income, and the Income elasticities of demand for food; the size of the country, the population distribution within It, and the rate of population growth; the country's socio-economic structure and its politico-economic ideology (the environment for private investment and the ease of entry Into marketing enterprises) . Many authors have made important contributions about the role played by the variables that influence the distributive sector and the contribution of this sector to the process of economic development [1, 2, 3, h, 5, 13, 1^4, 16, 18, 28. 31, 3^, ^0, h] , kl, 43, hk, kb, k3, 57, 64,

PAGE 66

48 66, 67, 73, 79, 81, 83, Sk, 86, 88, 90, 97, 100, 102, 103, lO'*, 105, 110, 112, 115]. Drucker [28, p. 3'*^] assigns marketing such a critical role in the development process as to consider it to be the most important "multiplier" of such development. Though often neglected, market system development makes possible full utilization of existing assets and the productive capacity of an economy, mobilization of latent economic energy, and development of managerial talent. Moyer [83, pp. 7-19], however, summarizes well the existing literature in several propositions about the role of the marketing system and marketing institutions. He suggests that they can provide the necessary means to coordinate production and consumption and provide consumers with the commodities they need and want. By making available new or improved products, improved marketing systems can increase the elasticities of supply and demand. Market systems can also reduce risk by providing more adequate information flows among participants in the system. Secondly, markets can incorporate subsistence producers into the exchange economy and also be an important channel for entrepreneurial talent and capital for other sectors of the economy. Third, as a result of market extension, market systems may generate pecuniary and technological economies, both internal and external, for producing firms. Efficient markets can lower consumer costs by improving distribution efficiency, more intensive resource use and less spoilage. They can also reduce transaction and exchange costs between producers and consumers. Most important, and closely related to the problematic situation in this research, is the fact that marketing can "produce" just as

PAGE 67

A9 farming does in the following senses: reducing losses to consumers is the same as increasing yield; storage augments production for the off season; providing timely inputs to farmers also increases yield; improving quality increases val ue (price) though often for marketing agents beyond the farm level. Transplanting marketing strategies from the industrialized countries to the developing countries should be avoided. Currie [18] has shown that it is ill advised to assume a standard pattern of development for all countries and that trying to apply the marketing organizations and techniques of the developed countries to LDCs will not render satisfactory results. This is due to an array of differences in marketing efficiency between the two groups of countries according to Chaturvedi [14, pp. 118-23]. While in developed countries the producer is relatively prosperous, and is linked to and depends upon, the market, the self-subsistence farmer of LDCs is not. While in the advanced countries the main source of income of the middlemen in marketing is their turnover profits, in LDCs the often numerous and small middlemen generally depend on their margins for their incomes. Differences in transport and communications, information, storage, grades, and standards, etc., also prevail between the two types of countries. For these reasons it is clear that a transplant of techniques from advanced countries to developing countries will not necessarily produce satisfactory results. In traditional economies, on the other hand, marketing firms play a passive role by merely buying and selling. They can be positive and play a major entre-

PAGE 68

50 preneurial role. Development of the banana marketing industry in the United States started by a ship owner looking for products to haul back to the U.S. from Jamaica who was later joined by other food merchants, is a good example. Marketing and the Theory of Demand in LDCs A special consideration must be given to the relationship between marketing and the theory of demand in developing countries. The importance of the application of demand theory to developing country problems is accentuated by the introduction of new technologies coupled with a complete lack of knowledge about demand conditions for the different commodities. The excessive variability in the quality and volume of supply can be a tremendous problem for producers and market organizers in these countries. The law of demand states that, ceteris paribus , quantity demanded of a commodity varies inversely with price. Chaturvedi [\h, pp. 131-2] has pointed out several reasons why the law of demand can present special characteristics in LDCs. The law of demand assumes that conditions regarding the means of transport and communications are similar everywhere. Nevertheless, it sometimes happens that In LDCs, when transport difficulties occur, price increases are present when demand in a region has risen even though supplies of the commodity are adequate. Another characteristic present in LDCs is the fact that, particularly for foodgrains, movements of some commodities follow the directions of the profit

PAGE 69

51 trends or the expectations of the middlemen without considering consumer needs. This may result in surplus in one area while there is a need for the commodity in another area which lacks the necessary purchasing power. Knowledge of demand conditions are of foremost importance for planning in developing countries. Abbott believes that ...the first stage at which market considerations enter the planning process is forecasting probable demand as a basis for fixing production targets. While looking for potential resources to exploit is one of the first elements in any plan to accelerate economic growth, decisions on how to use these resources and at v/hat pace to put their products on the market must depend on an appraisal of the demand. This includes both the demands of a growing domestic population and the demands of international markets in which a country hopes to sell as a means of earning the foreign exchange it needs for development .. .Where less familiar or more specialized crops enter a plan, careful attention to consumer tastes, preferences and habits is essential. Examples of misjudgement on such grounds are common [1, p. 9^]. It is necessary, however, that the market demand provide production incentives. Of special importance are, according to Abbott [1, p. 102; 2, p. 365], first, reasonably stable prices (without discontinuous intra or interseasonal changes) at a remunerative level. Farmers will hesitate before incurring additional work or expense to increase production unless they have confidence that prices will be higher than costs. Second, adequate marketing channels and facilities must be provided at the proper time. Farmers will be disappointed if they see that their increased ouput cannot be sold due to the lack of a proper channel. Finally, a satisfactory system of land tenure avoids large share of the returns from increased output going to the hands of the landlords.

PAGE 70

52 To avoid marketing problems in the future, research on demand conditions must be conducted. This should include both domestic and foreign demand. Knowledge of price and income elasticities of demand can be used to signal producers where, when, and what products they should produce. Marketing and the Theory of Supply in IPCs Of special interest to our concern about traditional and commercial farms and crops' response to improved technology is the relationship between marketing and the theory of supply In developing countries. The law of supply states that, ceteris paribus , quantity supplied of a commodity varies directly with price. Developing countries often emphasize increasing production of food crops by relying on modern yieldincreasing technology. Adoption of the new technology is supposed to foment increased productivity and product ion [26] . Technological advance, however, may bring about productivity increases yet the same level or declines in aggregate production. Due to major seasonal and cyclic price fluctuations mainly in basic grains and to small farm income limitations, small farmers In LDCs choose, quite rationally, to grow only enough of some food crops for home consumption. Policy makers often desire to secure for the country adequate increases in the marketed supply of food crops and to determine necessary 2 future changes in land utilization to meet that objective. Knowledge of ^The Impact and implications of foreign surplus disposal In developing countries are voluntarily ignored. The interested reader is referred to some of the relevant literature [33, 62, 63, 91, 109, HI, 121].

PAGE 71

53 total and market supply response by traditional and commercial farms to changes in production, price and income under different regional conditions has concerned numerous development economists. Major contributions to an understanding of the forces governing supply response in "subsistence agriculture" are provided by Wharton [119], Behrman [11], and Krishna [68, pp. ^97-5^7]. The latter has provided a comprehensive analysis about agricultural price policy and economic development, mainly concerned with supply response and price determination in developing countries. The behavior of farmers in developing countries relative to a marketable surplus has been the main focus of several recent more general studies. Included in this research are the relationships between marketable surplus and dual development [23], marketable surplus and economic growth [29], and marketable surplus, dual development, and economic growth [122]. The relationships between marketable surplus and price [60, 72, 11^], size of land holdings [87] and stages in the process of development [78] have also gained special attention. Numerous specific studies related to production and supply of traditional and commercial crops, annual as well as perennial, mostly concerned with estimating the sign and magnitude of the price elasticity of the marketable surplus, have been conducted [6, 7, 8, 9, 10, 15, 20, 21, 38, 39, 50, 60, 61, 69, 70, 71, 76, 77, 85, 99, 113, 116]. The results generally suggest that the inverse relationship between surplus and 3 The author does not want to discuss the acceptability of using the concept of "subsistence agriculture" so broadly. Miracle [82] considers the use of the term erroneous since agriculture in LDCs, according to him. Is not homogeneous.

PAGE 72

5h price found in some cases can be attributed to two possible causes. One is tied to the relatively fixed demand for money by traditional farmers which calls for sales only to the level of money needed. The second cause is that increasing traditional crop prices may stimulate an increase in the farmer's income such that the income effect on his demand for consumption of the crop outweighs the substitution effect in production and consumption [78]. For ei ther cause, marl
PAGE 73

55 The need for a theoretical and analytical framework to enable economists to analyze the total small farmer basic economic system is evident. Such a framework would be an important contr i but ion to the development theory. This research attempts to provide a basis for more fully understanding supply response criteria inherent to traditional and commercial agriculture in developing countries.

PAGE 74

CHAPTER t I I THEORETICAL AND METHODOLOGICAL FRAMEWORK FOR INVESTIGATING TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE The basic economic system of the Guatemalan small farmer is described in the first section of this chapter. A second section contains the method of estimation with the corresponding hypotheses and equations and the description of how the model has been adapted to the different regions of the country and the different cropping patterns. The third section explains the methodology used for computing input acquisition and product disposition. Finally, data used and implications are briefly di scussed . Basic Economic System of the Guatemalan Small Farmer The environment in which a Guatemalan small farmer lives determines his consumption and selling decisions. A small farmer grows basic grains mainly for home consumption. At harvest time he disposes of his production in several ways. A large share is kept for family consumption and other noncash purposes such as feed, seed, payments in kind, etc. If cash is needed, part of the output may be sold at the time of the harvest. In good years some production may also be saved to be sold throughout the year whenever the farmer needs cash or when high prices make sel 1 ing worthwhi le. 56

PAGE 75

57 The hypothetical price-income-consumption (PiC) path developed in Figure 5 (A) illustrates the small farmer's consumption and selling decisions and is used to develop his market supply curve for a product. Due to his subsistence needs, the small farmer's demand and supply situation for items produced on his farm is somewhat unique. Figure 5 (a) shows a hypothetical price-income-consumption (PIC) path for a commodity produced and consumed at the farm level. Assume the_ farmer is at point Z, where price is P and increases to P, . The farmer's income will increase. The income effect created by the price increase will mal<.e him move up and along the PIC path. Most food crops produced on the farm can be considered as inferior goods; since small farmers usually have so little income, a small price increase may produce a significant change in his income position such that he is willing to consume less of the product. Since he is his own supplier, he can cut back on his consumption. If the process is repeated, the hypothetical priceincome-consumption (PIC) path shown in the figure can be drawn. Total output is fixed at OB and the amount OC is the minimum necessary for family subsistence and seed for the coming season. If quantity OB is desired for home consumption and other noncash purposes, the farmer will not sell any output. However, cash needs or higher prices throughout the year might induce him to sell some of his product and forego some consumption. For example, if the price is P., the farmer keeps OA and sells AB. The decision process at harvest time and for the short-run, depicted in Figure 5 (B) , is dependent primarily on product price, home consumption needs, and cash needs to purchase other goods. At harvest total supply is Q, . If the price is P., the farmer expects to consume OA.

PAGE 76

58 OCA PIC B Q (A): Firm--Long run priceincome-consumption path A PIC B, Q 2 "l "1 (B) : Firm--Short run home vs< sales M „H „T C (C) : I ndustry--Priceincome consumption path AB CDMTQ (D) : I ndustry--Market supply Figure 5. --Guatemalan small farmer consumption and selling decisions

PAGE 77

59 H M (Q quantity used at home) and to sell A.B (Q quantity marketed). This decision at harvest time establishes OA and A B as supply and demand proportions for the year if price stays at P.. When all of the output is sold at harvest, no further decisions are possible. If the farmer did not sell everything at harvest, Q„ becomes the new fixed total supply curve since B„B was sold or consumed. At P. expected home use would remain at 0,. However, as price rises to P„ , home use Lj declines to Q„ or OA and sales are A B thus reestablishing demand and supply proportions. The process, when induced by increasing prices, may continue until Q reaches the amount where the hypothetical priceincome-consumption path becomes asymptotic to the Y axis at OC , the minimum needed for family subsistence and seed. It may happen that, as Q shifts to the left during the marketing period, prices above P_ result in decreasing quantities marketed. Little or no surplus available when prices keep rising may bring about indirect relationships between prices and quantities marketed. For price declines, the process is also operative and illustrates greater home use relative to sales for the short run or one season. From the hypothetical priceincome-consumption path for each small farmer, as illustrated in Figure 5 (A), a comgiunity of pr i cei ncome-consumption paths can be developed as in Figure 5 (C) . The effects of price and income changes, (e.g., constrained variables) result in movements along the path. Other variables exert an influence in the position of the PIC path. While increases in farm size and in the level of education with other things remaining equal, make the path shift downward, the opposite occurs as distance to the market and quantity demanded on the farm increase. If the profitability of other grains goes up, the PIC

PAGE 78

60 path also shifts upward. As the PIC path approaches the total production constraint (Q ) it becomes more elastic. At point Z, the elasticity of the PIC path is infinite; price is so low at this point that farmers decide to consume everything they produce since there is no incentive to forego consumption through sales in the market. M The hypothetical PIC path is used to derive the market supply (Q ) shown in Figure 5 (D) . By starting at point Z and moving up and along the PIC path, quantities marketed at different prices can be read to establish Q . If the quantities used on the farm (Q ) are added to Q , the total quantity produced (Q ) is identified. At this point, Q does not present the completely vertical shape that the fixed total supply curve shows in sections (A), (B) , and (C) of Figure 5. Although Q is a fixed amount until the next harvest, it does decrease during the marketing period as the farmer alters his consumption and selling decisions due to changes in his income situation produced by price changes. For M M T that reason, when Q (OC or MT) i s addedtoQ , Q slopes upward. At P,, T M however, both annual supply functions (Q and Q ) are perfectly inelastic and will not be affected by further price increases. Here the basic MTU identity Q. = Q Q will not be subjected to further alterations until the following harvest. Since there is an infinite number of hypothetical Income level and farm area devoted to the crop in question provide offsetting influences on Q which are not measured in this research. As income rises with an income inelastic demand for a basic grain, consumption per capita at the farm level may decline while demand for seed may expand until the income supply response function Q becomes perfectly inelastic. For this reason a fixed Q is assumed.

PAGE 79

61 pricei ncome-consumpt ion paths, representing numerous farm families, and of combinations that can be made between Q and Q , and since Q shifts M over the marketing period, there is an infinite number of possible Q M M curves as shown by Q to Q in Figure 5 (D) . Since Figure 5 (D) is derived from Figure 5 (C) , the starting points of all industry supply functions are completely elastic; such a low price does not induce farmers to market any output. M T Assuming that Q and Q in Figure 5 (D) are two observable supply functions, small farm market behavior can be further investigated. At price P., OT is total quantity produced (Q ) , AB is the quantity kept at home (Q ) and OT minus AB is the quantity marketed (Q ) . As price goes u up, Q will fall until it reaches the minimum amount MT . At P , for example, OT is again total quantity produced (Q ) , CD is the quantity kept at home (Q ), and OT minus CD is the quantity sold in the market M M (Q ) . Q is therefore not a fixed amount but becomes a function of price throughout the marketing period. Thus, knowledge of those conditions T M that induce changes in Q and Q are necessary to identify both curves and the implications of their relative locations and shapes. Since the levels of Q_ observed are not actually purchased in the market at different prices, we cannot obtain farm family demand functions, final equilibrium points, and demand elasticities. Interest, however, is in determining supply responsiveness to changes in farm size and level of income. Enterprise combinations utilized by small farmers at different income levels are closely related to the theory of small farm demand and supply of basic foods. More specifically, the impact of income changes on the relative quantities that are produced and marketed from

PAGE 80

62 the crop mix as \-ie]] as land use patterns support the demand and supply theory. This subsistence, land use and crop mix environment of the Guatemalan small farmer is characterized by varied levels of risk aversion as relative incomes change. With few, small and divided plots of land at his disposal, the small farmer grows primarily traditional crops although he may also produce some commercial crops where risk is minimal relative to that of other high value crops. As opposed to low risk traditional crops grown mainly for subsistence, low risk commercial crops are a source of income where adversity would not extend beyond normal weather fluctuations. Low risk commercial crops may also include crops whose prices are supported by the government. Wheat is a good example for Guatemala. The small farmer's behavior within his basic economic system is one of carefully balanced risk aversion, income maintenance and risk taking. As depicted in Figure 6, at very low levels of income or farm size the farmer grows basic grains for subsistence though he may also sell part of his production. The difference between total quantity produced (Q ) and quantity marketed (Q ) of a traditional crop depicts home use reu quirements for consumption, seed and other purposes (Q ) . Since crop t is mainly intended for subsistence, the curves show some income responsiveness at very low levels of income and almost none at high income levels. Because some grains will always be grown due to cultural values, (corn and beans are good examples), the curves will be similar in shape and, once the home use requirement is reached, the curves will tend to become perfectly inelastic (or vertical) regardless of income level.

PAGE 81

63 I ncome or Farm Size Quantity of basic grain Figure 6. -Income-quant i ty or farm size-quantity relationships for the Guatemalan small farmer, given his land constraint

PAGE 82

64 As income rises, due to productivity and/or price reasons, the farmer will divert some of his land into other commercial crops (Q ) while maintaining c his sel f-sufficiency product ion on less land. In this case, the response will increase with income up to the point where the farmer has no more land available for crop production or it is feasible to introduce another commercial crop. Thus, as income rises, small farmers with their self-sufficiency guaranteed, will tend to diversify production by growing high value crops until the land constraint is reached. Q in Figure 6 is not produced until a certain minimum consumption and income level is attained with the basic and low risk crops. Income responsiveness of the higher value and higher risk crops is greater than for the traditional crops. At higher income levels farmers venture into higher risk crops and combine their production according to income level and land availability. Figure 6 Is also operative to determine land use patterns when the vertical axis Is labeled with different levels of farm size. Method of Estimation This section presents the methodology used in this study. The hypotheses to be tested with the corresponding functions and the adaptation of the model to the different regions and to varied cropping patterns are also explained. Hypotheses Since income-supply relationships are the main focus of this research, the primary set of hypotheses relates to the respective elasticities. The

PAGE 83

65 hypotheses are. formulated broadly since it may be the case that a traditional crop in one region may be a commercial crop in another region. The functions, and corresponding elasticities, will behave differently in each case. Concerning income elasticities of market supply it is hypothesized that: (1) When crops are grown for subsistence, at very low levels of income, small farmers will market very little. As Income rises small farmers will market more but only up to a certain amount where they have their self-sufficiency secured . (2) If the income of small farmers rises, they will produce and market successively higher value crops in combination with subsistence crops and within their land constraint. Concerning the productivity of basic grains and of competing or alternative commodities, it Is further hypothesized that: (3) If the productivity of basic grains grown for subsistence increases due to yieldIncreas Ing technologies, then small farmers will produce up to the point where they would have their self-sufficiency secured with less land. (k) At low Income levels, as alternative crops become more profitable, small farmers will produce and market wheat up to a certain amount after which they will shift to other commercial crops since their income cannot be increased much more due to the wheat price support limit.

PAGE 84

66 Concerning farm size elasticities of market supply, it is hypothesized that: (5) When farmers are at the very subsistence level, all available land is devoted to traditional crops. As technology or farm size continues to increase, small farmers will grow other crops while maintaining their self-sufficiency. Concerning price elasticities of market supply, it is hypothesized that: (6) As the price of basic grains rises, small farmers will market more output but the percentage increase In supply will be less than the percentage increase in price. Concerning production and distribution activities of traditional and commercial basic grains, it is hypothesized that: (7) If the productivity of basic grains can increase, and production gains are obtained at the same time, production and distribution activities can still be performed adequately. 2 The Model Based on the small farm decision process just described, the following market supply function can be estimated: M T 1 i (1) Q, / Q; = B^-^ B, P, + B^ Ef ^3 A. + B^ D. + e^ I. + B^ W. + 3_, Y. + e. 1 7 I I The Appendix contains a complete specification and discussion of the mathematical and statistical models.

PAGE 85

^7 where, M T Q. / Q. = percent of grain production that is marketed (l
PAGE 86

68 ratio equals one, while in a totally traditional farm it equals zero. A positive sign Indicates that the crop becomes more commercial as independent variables increase while a negative sign indicates a tendency to more traditional, or less commercial crops for the direct variables (E., D., I., W.) and the opposite for the reciprocal variables (P., A., Y.). Ill III The ratio also becomes smaller or larger at different price levels due to the total production constraint. Total farm size (A.) is included instead of area producing each crop (A.) to account for the differences in farm size and to illustrate variations in quantities marl
PAGE 87

69 From (1) we can write (3) Q J = QJ . Q J / q{, or w q^ = q':' . (q':'/qT) + 1. . (q':'/q"[) II II I II Sol VI ng for Q. , (5) (1 q'I'/qT) Q, = Ij . Qj /QJ Final ly , (6) q'J' = I . (q'I' / QJ) / (1 Q^ / QJ) Once (6) is obtained, it can be substituted in (2) and, after adding I . , Q. can also be obtained. I I Adaptation of the Model The model is adapted to specific circumstances in different regions. M T For example, when two crops are associated, Q. / Q. for both crops must be estimated. Price and quantity variables must be converted to weighted values to permit realistic comparisons and derive realistic conclusions. In the case of two or more associated crops the following weight Is used: Let TR. and TQ. be total revenue and total quantity of crop i, respectively, and TR . and TQ. total revenue and total quantity of crop j associated with J J crop i in one region. Then, ZTR. / ETQ. = P ., a weighted price for crop i in the region, and, I I Wl 3 r t3 » . ITR. /ETQ. = P ., a weighted price for crop j in the region. Then Q. . / 0. . may be estimated as the sume of P . . [Q. / Q.] and IJ "IJ Wl I I

PAGE 88

70 P . . [Q. / Q.], and Q. . / Q. . v;ili have been given a value figure. In WJ J J I J I J the case of price on the right-hand side of the equation, (P. . Q. + P. Q..)/ (Q. + Q.) = P..> a new enterprise price for an association. Production and Distribution Activities Description and quantification of production and distribution activities is illustrated In Figure 7These activities are explained for every enterprise in the different regions of the country. The figure contains amount (kgs) and cost (quetzales/kg) of the different inputs utilized in the production process and the different ways for disposing of total production. Since figures in each cell take into account the weight given to each questionnaire, they are Intended to represent good approximations of totals in the region. Data Used and Implications Not all farms contained in the sample are used in each of the estimated equations. Q. / Q. picks up only those farmers selling some of their output; or in terms of the theoretical presentation, those producing more than OC In Figure 5. Furthermore, it seems that the sample failed to include a considerable number of these farmers, and, since the sample was Intended for a small farm study, only very few of the large farmers were Included. For those reasons, the estimates are conservative. Responses will therefore be stronger than shown in the results since both ends of the spectrum are not considered. In Chapter six, a special section is devoted to the discussion of the descriptive statistics of each independent variable, and generalizations and implications of the resul ts .

PAGE 89

71 \-

PAGE 90

72 The computations of the production and distribution activites do encompass all farmers in the sample size. For that reason, averages in the activities, especially total quantities produced, may not coincide with those in the estimated equations. Summary This chapter has described the theoretical framework which explains the Guatemalan small farmer's behavior within his basic economic system; a sytem in which his subsistence needs, the land constraint, and his Income level are the most important variables. The production and distribution activities to be described and the equations to be estimated attempt to quantify that behavior by considering the variables that may be relevant to his decision mal
PAGE 91

CHAPTER IV PRODUCTION AND DISTRIBUTION ACTIVITIES Production and distribution activites for each basic grain or association produced in the different regions of Guatemala are described and quantified in this chapter. The description by crop, or association, follov;s the pattern of analysis utilized in Chapter five. Characteristics or each crop or association are identified for each region to facilitate interpretation of the results presented in the remainder of the dissertat ion . The Input Market Input use in basic grain production is presented In Table 8. After briefly defining each production activity, the description focuses on the relative importance of each activity across enterprises and regions (Table 9) . Seed Ut 1 1 i zat ion The activity of seed utilization relates to the total amount of seed purchased at planting time or stored from a previous harvest. Some differences in seed management across regions and crops are present. Of all the associated enterprises, corn-beans in R and R^ 73

PAGE 92

Ih CO
PAGE 93

75

PAGE 94

(0 E v 0) >^ c o o •o o c I. cn u un (0 J3 o (U 3 D. C 4) O O. B > a: 0) o a: o v^ LU Ci LTV 76 < m

PAGE 95

77 T3 0) c O o ro

PAGE 96

78 Is the heaviest user of seed per hectare. Corn-beans in R and R is most dependent upon stored seed. Land scarcity in R calls forth more intensive production of corn and beans as single crops, evidenced by the highest application of seed per unit of land. This region also depends more on stored corn and bean seed than the remaining regions. In rice production, average seed use per hectare is higher in R, 6 than in R and R, while R depends more on purchased seed. The main difference found in wheat production is an almost complete dependence on seed purchased In R^, as opposed to an even distribution in R , the latter being a more subsistence region that the former. Also, less wheat seed is used per hectare when it is purchased than when it has been stored. In general, seed becomes linked to product sales, seed storage, and seed purchase decisions. Thus, variation does prevail in the percentage of total production retained to be used as animal feed and seed and that percentage of seed which is purchased (Table 10). Urea Appi icat ion Average amounts and cost of urea per hectare suggest that usage of this input is fairly common. Although urea application appears for all crops, except for beans in R, , some of the crops contain only a small number of observations; these crops are wheat in R^ , D corn in R , beans and rice in all three regions, sorghum in R,, and corn-beans-sorghum in R,.. For the remaining crops, no major differences in either average use or average cost of urea per hectare are found.

PAGE 97

79 Table 10. --Seed purchase and sale proportions relative to total production and total seed use CROP^

PAGE 98

80 Use levels do differ between associated crops and single crops v;here rates per hectare average hj.h kgs and 119.3 kgs., respectively. Soi 1 Add i t i ves This activity, with use limited to only four crops, contains amounts of calcium oxide and other soil correctives applied. The appearance of only three or less observations in every case signals the extremely limited use of this chemical input in basic grain production. Other Chemicals Application of chemical fertilizers other than urea is heavier than that for any single input as evidenced by the use of chemicals in all enterprises. Average costs per hectare are the highest in wheat production in both R. and R^ , and the lowest in all associations and in rice in R . The remaining crops utilize similar amounts per hectare. Again associated crops utilize only Q9.6 worth of chemical fertilizers per hectare compared with Q25 for single crop enterpr i ses. Other Pert i 1 izers This activity encompasses the utilization of other fertilizers, sprays, etc., which are recorded as an average cost per hectare. Very limited observations of use for each enterprise confirms the minor role of other fertilizers in basic grain production.

PAGE 99

81 Pest i c ides Under this activity, average cost per hectare of applying insecticides, herbicides, and other chemicals utilized in pest control are recorded. Although used on every enterprise, pesticide application is not very generalized among farmers. Average cost per hectare for pesticide use varies substantially but is particularly high at Q12 or more for rice in R, and beans in R, and R . Most enterprises and regions display pesticide costs at less than Q5 per hectare. Pesticide costs per hectare for single crops average Q7.1 compared to Q.2.2 for associations. Labor Labor utilization encompasses all phases of agricultural activities, from soil preparation to harvesting and marketing the finalproduct. Since it contemplates cash payments as well as family labor, the word jornal used in the questionnaire is assumed to mean man day. Except for the associations, where employment per hectare is very similar, all enterprises show different levels of employment by region. In corn production, R and R employ more workers per hectare than R, , R , and R^. For beans, R is the largest employer, while R and R^ use more labor per unit of land than R, in rice production. Wheat production requires more labor in R than in R,. For all of the crops present, R, is the largest employer. Perhaps this is a result of the subsistence nature of the region. In general, however, associated crops utilize substantially less labor (kk.2 man days per hectare) than do single crops (75.8).

PAGE 100

82 The Product Market Distribution of total basic grain production is presented in Table II. Emphasis is given to the relative importance of the distribution activities and the major differences encountered across crops and regions (Table 12). A brief definition of each activity is also presented at the beginning of each sub-section. Total Production Average production per hectare, differing among enterprises, is very similar for each particular crop grown in different regions. Yield differences, of course, are correlated with the nature of the crop. For the associations average production per unit of land is very similar across regions. However, when the same crops are grown alone, corn and sorghum exceed the association yield levels while bean yields fall below those of the associations. Rice production shows no major differences in average production per hectare across regions. in wheat yields are somewhat higher in R than in R, probably resulting from heavier chemical input usage. Animal Feed and Seed This item pertains to that part of total production set aside by the farmer to be used as seed in the future or as animal feed. The activity is a fairly generalized practice as evidenced by a large number of observations obtained in each crop, with the exception of wheat in R,.

PAGE 101

83 r^ .— — ^ CO -— ^ -^ ^-^ o . — ^ CO-— ^or^csi-^--zrro cm -dvD-a-coocofNj-^' r-• \o -cNj -o '
PAGE 102

8i« cvi cvi cr> r-en • o o CO r^ — -a-3vO O — s vO ^-^ CNI cvj VO LTV r^ . — ro-T O CTi n£) * o • cr\ • o -co -^r o r^ o — u-»— • --' \£) ro —
PAGE 103

E ro O CO I <_> IS -O 10 o 3 J3 V u c m u o ex E (U a; J3 ID 85 o UJ cc: — > — < CO I — CO vT)

PAGE 104

86 CM -3-3o Jo CM OO -3OO en -3CO

PAGE 105

87 The average amount of rice production per hectare saved for seed and animal feed purposes shows some regional variation among enterprises. The corn-sorghum and corn-beans-sorghum associations of R^ save more than twice the amount saved from corn-beans of R, , R_, and R^ . In I 5 o corn production, R. saves the least for seed and feed purposes, while all regions keep a similar amount for bean production. Concerning rice, R, and R_ save an identical amount, while that stored in R^ is H 5 6 somewhat higher. Family Consumption The amount set aside at harvest time for the sole purpose of family consumption is contained in this activity. Average family consumption of basic grains, with the exceptions of wheat and rice, is relatively large and does not show major regional differences. Average family consumption along with total production is lower in the corn-beans enterprise of R^. than in the rest of the associations. In corn production, R_ and R, show a somewhat higher consumption than R, , R^, and R^ , while in beans, R, and R_ save less for future home I i) b I i) consumption than R, and R^. Rice consumption is higher in R^. and lower and nearly equal in R, and R,. Wheat is not consumed in R, and very few observations appear in R . Process i ng Throughout Guatemala a very minor amount of basic grains is set aside at the farm level for processing. Only one observation, each

PAGE 106

88 in corn of R^ and in beans of R , and two observations in wheat of R. , appeared in the sample. Rent Payments The product distribution activity of rent payments includes not only payments made for the use of the land but also payments for equipment and house rentals. Although this practice is found throughout the country, the small number of observations in the sample leads one to believe that it is not a very common practice. Corn is, by far, the most important crop in this activity. Sales "in Kind" That part of production exchanged for goods and services other than cash or rent payments is included in this activity. Corn is again the crop most commonly used for this purpose. The small number of observations per crop again suggests that this is not a very generalized practice. Donations Included in donations is the amount of total production given to relatives and friends for which no renumeration was received. This practice is more common than rent payments and sales "in kind". Corn again is the crop most used for donations. Total Losses Production damaged, lost, or stolen after harvest appears in all crops with the exception of rice in R, and corn-beans-sorghum in R^.

PAGE 107

89 However, failure of interviewers to consistently record losses makes it difficult to assess the relative variation of losses among crops and by regions within crops. Cash Sales Sales for cash cover all production disposed of in exchange for currency. Variations depend on farm demand for production and consumption purposes. Average sales per hectare, among the associations are higher in the corn-beans enterprise of R^ than in the remaining associations. Being the basic subsistence cropping pattern, with high levels of home demand, associations present lower average sales than the rest of the crops. Corn sales are similar in all regions except for R, where they are somewhat lower. Average cash sales of beans per hectare do not present sharp variations, excluding a lower amount in R. . Rice sales are very close in R, and R^ but somewhat higher in R . Average cash sales of wheat per hectare do not vary substantially between R, and R^. Marketing Expenditures Expenses incurred by the farmer in marketing his products include the cost of containers (boxes, bags, etc.) and the cost of transporting the product, either by truck or animal, from his farm to the market. Although marketing expenditures per kilogram of product sold are generally one cent or less, differences are observed when these expenditures are expressed as a percentage of the average price received

PAGE 108

90 by the farmers in the region. Enterprise variation in marketing costs from greatest to least are wheat, rice, sorghum^ corn, followed by the associations and, finally, beans. R tends to experience the highest marketing costs followed by R, and R , v;h i 1 e R. displays the greatest b 3 D amount of variation ranging from 1.5 percent for beans to 10.2 percent for rice (Table 1 3) • Summary Production and distribution activities of basic grains reveal major differences among crops and regions. Some of these findings are used in the analyses £nd implications in the chapters to follow. Production of basic grains from the input standpoint is most influenced by seed and fertilizer costs. While fertilizer tends to be universally utilized, but at different levels depending upon crops and regions, soil additives and pesticides are used to a minor degree. Seed becomes closely linked to product sales, seed storage, and seed purchase decisions. Corn, rice, and wheat are the crops employing more workers per hectare, followed by beans and the associations. Except for the associations, where employment per unit of land is very similar, all enterprises show different levels of employment by region. Total production also presents differences among crops relative to yields and product distribution. Average production per hectare is very similar for each crop grown in different regions. However, when the crops of the associations are grown alone, yield rises above the average for the associations for corn and sorghum while bean yields are below those of the associations.

PAGE 109

91 Table 13."~Market ing expenditures as a percent of average price received by enterprises and regions CROP REGION 3 h

PAGE 110

92 Average family consumption, excluding wheat and rice, is relatively large and does not show major regional differences. Production set aside for processing, sales "in kind", and donations are rarely present with corn being the most important crop used for these activities. Variations found in cash distribution category depend on farm demand for production and consumption purposes. For example, being the basic subsistence enterprises, the associations present high levels of home demand and, therefore, lower average sales than the rest of the crops. Expenditures per kilogram of product marketed are generally one cent or less but, when expressed as a percentage of the average regional price, from highest to lowest, the ranking is wheat, rice, sorghum, corn, the associations, and beans.

PAGE 111

CHAPTER V TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE To explain and analyze the results obtained from the empirical model is the objective of this chapter. Regression coefficients are interpreted, the computed elasticities are explained, and income, farm size, and price-quantity relationships are discussed for each basic grain or association grown in each region of Guatemala. A summary of the results at the end of the chapter serves an an introduction for the discussion of the implicat ions in the following chapter. Associations The corn-beans association is found in R, , R^., and R^ , while the I i) b corn-sorghum and the corn-beans-sorghum associations are only present in R,. The regression coefficients obtained for each of these associations (Table 14 and Table 15), the income, farm size, and price elasticities (Table 16 to Table 18), and the income, farm size, and pricequantity relationships (Figure 8 to Figure 10) strongly support the conceptual model by illustrating the typical behavior of traditional enterpr i ses. 93

PAGE 112

3h o -3O LA O -3oo — — -3in LA PA o rA CO

PAGE 113

CM 95 -3vO

PAGE 114

96 Table 15. ""Sign and significance level of the regression coefficients for each basic grain or association by regions of Guatemala

PAGE 115

J3 O o o C to a. a. 3 0) E o J3

PAGE 116

98 CM vO rr> — LA — OO^LTvrocNi' — ^-i — OOO COtNIOOOOOOOOOO OOOOOOOOOOOO oocsj-croo^r-rr^r^covr)— — Ounr^co rNlC0p^-3--^OO(N ounxOp^cNi. — . — ooooo >XI— OOOOOOOOOO oooooooooooo -TcoocNir^covoo — crvoo-3— r^cn— . — cnM3csir^-3- o a)
PAGE 117

S9 CO CNi roa3 r^Lncn^T — cnr-^vo ltv-t-t ro ^^4f>~^Ol^\^o^^l — ^-. — OOOOOOO cr\oj — ooooooooooooo OOOOOOOOCDOOOOOOO (0 E (U Q Si c o o o sz Q. Q. o o J3 corvjvo — ^oa>c^o^^Jv£>ocNl-^rovDo ^o-cr crivovr>-3unjr>jvo un^o cn^r c^vjd LTNvO ro— \n CO r^O0Dv£3 Ln^r r»-\r^(NI cnj vDvOi — ^.zTCNI — . — . — OOOOOOOO ^JD oooooooooooooo vo — r~.cocor-~-3-cvjOLA ^ u\kO r^co -3"' — c-JcNjG^Ln-3-o^r-^cNr-j^-r-^coroo cNjoOLn-cro~^^o^rrocNics|i — . — • — . — ^-o r^LAcM — OOOOOOOOOOOCD ^ocnoo — o — L.-\-3-Ln — ooo 3urvoorMcsivor^Lnor*^ — cnilao^Dc^O unco r^cvi o-T ocovo Ln-^-mr^cvj csi cm ^CNi Lr\ r^ CM 0000000000 o LU or o LA. 3LA-T-aLA— u^c7^J-oo r-» a-o -:3-MD G^\o — r---o-^ Lnr^r^. — cno csi^o CO-3O r^r^c^J-:rCO-^ —~ CPvCOvDvO Lr\_3r^cr>rAr-*-^rAcNj — . — . — 000000 — CM'—OOOOOOOOOOOOO rsiLp,oocncr\ocor~cMo<-Aoo-3-o-3OOO^CTv-^— OCPiPAC^JOO-^LnoCNICOcv^ cr\cncrir^— ocx3 cncN cnco i^^o^cm^o cnj r-^^ •— — r>-irAv£)fNJOCOvDLn-J^r r^fv-\ cMocni-A'^cM^o — 0000000 00 — ^D — r^r^^a. — cap^njd lala-3LAcocNir^-^rArg — . — . — oooooo CNi vO CA -3^ CO CO — r^v^ LA rA — — 00 LA — CM CM CO cn O CM — — 00 -q, — 00 vn o-> — — ro r~vO rA c^j o o LA J-T C^ I 3VO ^O ^• vO M3 O CO . CM O O — CM 0000000000000 OOLACOCr\LACAvOCMCr».^CN]OvOCA^r— r-^cncn-3LAcnnAvj^oo^o o lap^laoo-t OALALA»^OvOrA-3— CMvDcMCOLAPA. — O vOvOCA^OOr^LA-^rAcMCN' — — •— • — \X) vD eg CM — 00000000000 LAOLAOLAOLAOLAOLAOLAOLAO CMLAr — OCMLAr^OevJLAr^OCMLAr^O 000 — CMCMCMCMeACArArA-T r-~ cnco ro o r»^ O O OA CM rA . — — 00 rAOO r» CA-a" cr\ r~o"\ cn LA 00 CA CA O O CM — VO (30 r~^ r~. -T CO CM r«-\ o (n CX> CM O rA — CO -T vO rA CM LA — O CM — — 00 CO -JD — 00 cr\ CM 1 vO -^ O CNI rA — LA CM LA O LA CM LA i —

PAGE 119

101 E TO JO c o u o -O OQ. Lr\r^o ~'Oa>or-^rNi\0rvlG~i00vr)u-v-3-.4r oooooo o J-cv-v(v^t^ csir^Lnroo-j — — OOOOOOO 'J^— OOOOOOOOOOOO ooocDi-n 3--crcr\ooLAcr\>.Ovocri • — CO l-^G^co^o o^-^ — or^^cr\r^r»-\(NjcMi — . cAvx>rsi ooooooooo . — coog^ooocNjLnrocnLncsi LnvDOO>U-VLrvj--3--— — -3-00.3— -J r^^r> ir\ ^T} — co^r>LA-3-rocMcsjcsi — 0-3-CSI — — OOOOOOOO -^ — 0>00000000000 o -O 0) r^vOCTicMLTloO 3-r^Ocv^\Dcr>CM OOO — — — tMCNICSIrOf>->r^<>-\.jOOOOOOOOOOOOCDO o u m CTl U> O r^ — r~. oo O LPt vO CO VD — O O O O O o r^ CTl LA (Nl cry -dlA — r^co — c-4 cn-aCM — — OOO i 3(SI -3r^ a> -T CM r^ vI3 vO CP\ -aro — o — OOO r»^ CO r^ ro I — -IT vO — O O O O O o o o o o CN lA r^ CT\ -^ r^ CM LA r^^ _3LA CO ro rA — o — OOO -3vo \o rv, CM O r^ r^ CM PA — O — OOO O O O O CM cr> c» CO r~~ en — C3D -3O vO rAoO t-~. (TV LA CA — O CM rA LA CO LA — cn I — CO I — ^ O -— CO -r CM — — OOO -3vo i^ r>. CM o -3r~. O LA -T CO CM LA CM t*^ oo -3CM OA f^ vO CA CM O O O — o o o o

PAGE 120

102 o o 0) J3 trO(T\-^t-r\LA. — OCMvO — CM — — ooooooo oooooooooo oooooooooo r-^rocTiO-T cnvo ro. — cr\ r^cnrorocj — . — . — . — o oooooooooo oooooooooo — — CNl— CNJCOCMmr^LTl cry — oroco-TcMOoor-~ Ln^rrorsj — — . — — OO OOOOOOOOOO OOOOOOOOOO oocn-3— o-\r^v^un-3--:r tNl — OOOOOO OOOOOOOOOO OOOOOOOOOO OOOOOOOOOO ofM . — ^-CNjCNlcMrorOf^'Ar^-:r oooooooooo lU > o Q. <0 SI s J3 o

PAGE 121

103 o o CM CM O O CO o o o o o o o NO o o CM (jeDA/sa[BZi3nb) aiuoouj

PAGE 122

104 ro r^

PAGE 123

105 CNI (0 E (U t3

PAGE 124

106 Regression Coefficients The regression coefficients of the five equations empirically tested for the associations, behave in general as hypothesized. Total family income (Y ) , except for corn-sorghum in R. and for corn-beans ' b in R , presents high levels of statistical significance. Total farm size (A.) is less significant for corn-beans in R and corn-sorghum in R^ than for the remaining associations. Quantity demanded on the farm (I.) shows marginal stat i st i cal s i gn i f icance for corn-beans in R^ and high significance for the remaining enterprises. Price (P.), as expected for traditional crops, appears with the lowest level to no statistical significance. Due to the reciprocal nature of the specification, the negative sign for total family income (Y.), farm size (A.) and price (P.) signals the presence of a direct relationship between each of these variables and the dependent variable. Only total income in the corn-beanssorghum equation of R^ has an unexpected sign. Of the three associations in R^, corn-beans-sorghum s'ee^ms to be the most traditional, which may explain the unexpected sign. Surplus in this case may be in fact inversely related to total income because higherincome farmers do not cultivate this association. The three remaining variables, education (E.), distance to the nearest market (D.), and the relative profitability ratio (W.) provide minor contributions to the model . All education coefficients are positive; it is expected that as the level of education increases farmers

PAGE 125

107 become more involved in the activities of the monetary economy and, as a result, market more of their output. Levels of statistical significance for education, v/hen present, are very low except for corn-beans in R^. Distance to the market (D.) presents no statistical significance in the corn-beans equations of R. and R,, minor levels of significance in the corn-sorghum and corn-bean-sorghum equations of R^, and a high level of statistical significance in the corn-beans equation of R . Distance coefficients alternate with positive and negative signs. Although a negative sign is expected, it is possible that the numerous middlemen arriving with their trucks several times a month at different places in rural Guatemala tend to eliminate a negative relationship between surplus and distance. Distance in the data used for this research, however, was defined as the distance to the place where the family most commonly buys and sells, which may or may not refer to the place where they sell the specific grain. In the relative profitability ratio (W.), high levels of statistical significance are found in the corn-beans equation of R, and in the corn-sorghum equation of R.., and none in the remaining equations. A positive sign for the corn-beans association in both R. and R is expected. Since corn-beans is the basic subsistence cropping pattern in R. and R with only one commercial crop in the numerator of the ratio for each region, the ratio and the surplus should move in the same direction. Wheat and rice, respectively, are the commercial

PAGE 126

108 crops in R, and R . In R^ three associations with both commercial and traditional crops in the numerator of the ratio provide confusing results evidenced by a positive sign for corn-sorghum and negative signs for (W.) in the remaining two associations. Income-Quantity Relationships As expected, the income elasticities of market supply indicate that all of the associations are quite responsive at very low levels of income (Table 16). The responsiveness, however, decreases sharply as income rises, which is an easily explained phenomenon. Farmers at subsistence experiencing an Income increase devote new resources to production and react by marketing the newly created surplus. At higher Income levels, however, responsiveness tends to decrease abruptly for traditional crops andoncethe home use requirement is met, commercial crops enter the production system. Figure 8 illustrates that process and corroborates the conceptual model by displaying the same pattern of behavior for all the associations in the different regions of the country. That Is, their appearance at almost zero income, their elastic portions at low Income levels, and their almost vertical shapes at higher levels of income, are characteristics that were hypothesized in chapter three for those crops belonging in the traditional category.

PAGE 127

109 Farm Size-Quantity Relationships Farm size elasticities (Table 17) and farm size-quantity relationships (Figure 9) for the associations parallel the income elasticities and income-quantity relationships except for the corn-beans-sorghum enterprise in R^. In the case of farm size elasticities, as hypothesized, responsiveness is more accentuated for traditional crops than for commercial crops at low levels of farm size. The corn-beans-sorghum association of R, presents an elastic portion up to 2.25 hectares, a level much higher than the remaining enterprises, perhaps due to the importance of sorghum as part of the human diet in R^. The vertical nature of the functions beyond low levels of farm size, further corroborates the traditional presentation of chapter three. Price-Quantity Relationships Associated enterprises, being the traditional subsistence cropping pattern, present very little price responsiveness (Table 18 and Figure 10), All associations show a higher response at low price levels than at higher prices and this finding is most accentuated in R^with corn-beans-sorghum. No available surplus at the end of the season when prices are high may contribute to this result as illustrated in Figure 5 (A) where Q shifts to the left during the marketing period. Corn In terms of acreage, corn is the most important basic grain in Guatemalan agriculture. Besdies appearing in al 1 associations , corn is cultivated as a single crop in all regions of the country. The dual character of this enterprise, being both traditional and commercial, is shown by the regression coefficients (Table 1^ and Table 15), and the income, farm size, and price elasticities of market supply (Table 16 to Table 18). The

PAGE 128

no income-quantity (Figure 11), farm size-quantity (Figure 12), and pricequantity relationships (Figure 13) uphold the former finding and support the basic theory of chapter three. Regression Coefficients Total income, total farm size, and quantity demanded on the farm carry the expected signs in all of the corn equations. Except for farm size in R^ and for quantity demanded on the farm, all of the coefficients present high levels of statistical significance. The price variable, however, displays the highest levels of significance in R, , R , and R, but also unexpected signs. The opposite occurs in R and R, where price carries the expected sign along with no statistical significance. Education shows the expected positive sign in all corn producing regions with the exception of R, but marginal significance in R-. and the highest level of statistical significance in R . Distance to the market is only significant in R, and R but carry opposite signs, possibly for the same reasons as given for the associations. The relative profitability ratio shows no significance in Rj., low in R , and high levels of statistical signifiance in the remaining three regions. The signs of the ratio vary according to the traditional or commercial nature of the crop and to the nature of the remaining crops grown in the region. In R. corn is traditional and in R, both traditional and. commercial, both having basically only commercial crops in the numerator of the ratio. Given these characteristics it is anticipated that the ratio and the dependent variable move in the same direction because self-sufficiency is not secured. Corn, being both traditional and commercial in R, and basically the only crop in the region (only a few observations of commercial crops are in the numerator) carries a negative sign possibly signaling that farmers, as

PAGE 129

Ill CTi CO E (0 C3 u^

PAGE 130

112 o o o O O o

PAGE 131

113 cr> 00 E QJ 4-1 CO D v^

PAGE 132

self-sufficiency is secured, decrease corn marketing and shift into more profitable crops. In R , both commercial and traditional crops appear in the numerator; for that reason, an inverse relationship is present. Finally, R, presents an unexpected sign compared to R where the crop has the very b b similar characteristics. Income-Quantity Relationships The income elasticities (Table 16) and the income-quantity relationships illustrated in Figure 11 reveal the traditional nature of corn in R. , R , and R,, and an accentuated tendency toward commercialization in R and R, . At very low income levels, corn is quite income responsive. The responsiveness tends to decrease more rapidly in R, , R^., and R. as a result of the traditional nature of the crop in these regions. In R and R, though becoming inelastic beyond the Q200 per year level, corn still shows some responsiveness at higher income levels. This responsiveness may be due to the diversity of chemical input usage, a situation only possible at high income levels, as identified in the production and distribution activities in chapter four. M Furthermore, the fact that commercial sales (Q.) begin around the Ql 50 income level denotes the subsistence character of this crop in these two regions at very low income levels. The dual role of corn in R, and R, is corroborated by a higher level of home use relative to the other regions. In these two regions, corn is cultivated as a single crop only, as opposed to the other regions where it also appears in all of the basic grain associations. Farm-Size Quantity Relationships Findings from the farm size elasticities (Table 17) and the farm sizesurplus relationships (Figure 12) closely parallel those of income. R^ and R. again display the traditional and commercial nature of corn.

PAGE 133

115 R, , R^., and R, grovv corn mainly for subsistence. At low levels of farm I b fa size, all crops are highly responsive, with the responsiveness decreasing faster in R, , R^-, and R, than in R^ and R, . The vertical shape of the 15 6 3 4 *^ functions in the former three regions means that subsistence may be secured and, since the crop is not commercialized, production and marketing decrease. The subsistence character of corn in R is given by its production at near zero farm size but sales of corn commence beyond the 0.^5 hectare size. The same reasoning applies to R, , where production takes place at almost zero farm size but marketing occurs only when farm size exceeds 0.25 hectare. These findings closely parallel the theoretical presentation of chapter three. Price-Quantity Relationships Though price elasticities for all regions are computed (Table 18) , only price-quantity relationships for R_ and R, are graphed (Figure 13) because unexpected signs appear in the remaining regions. In R and R. , corn is minimally price responsive despite i ts commercial nature. Being less responsive in R than in R, may result from prices being relatively lower than expected as evidenced by the heavy dependence on stored seed (95 percent of total seed used). Low prices may induce farmers to withhold more production than anticipated. The unexpected price sign for corn in R, , R , and R^ can be explained with the conceptual model of chapter three. Available output decreases throughout the marketing period as prices increase. Near to the

PAGE 134

116 asymptotic section of the pr ice-income-consumpt ion (PIC) path, higher prices may have resulted in decreasing quantities marketed, thereby leading to the indirect relationships observed between price and the surplus-output ratio. Beans Beans are cultivated as single crops in R, , R^, and R^ , where they also appear associated with other basic grains. This crop shov/s the behavior of a traditional enterprise, as given by the regression coefficients (Table ]h and Table 15), the income, farm size, and price elasticities (Table 16 to Table 18), and the income-quantity relationships (Figure 1 h) . Regression Coefficients All income coefficients in the three bean equations present the expected negative sign and high levels of statistical significance. Regression coefficients for the total farm size variable are also significant at high levels but present the expected sign only in Rj.. Unexpected signs in R, and R^ may be the result of omissions committed at the time of data collection, as has been recognized by AID officials (see chapter six), when interviews failed to specify some crops that were interplanted. Quantity demanded on the farm shows the expected sign in all equations, with a high level of statistical significance in R^, less significance in R5 and none in R . The price variable, showing different levels of statistical significance, carries unexpected signs in all three equations.

PAGE 135

117 o

PAGE 136

118 Education carries an unexpected sign in R , lovj levels of statistical significance in R, and R, and none in R . Distance being barely statistically significant in R , carries an unexpected positive sign in R, and R^ , possibly due to the role of truckers and middlemen ex1 6 plained in the discussion of the associations. The relative profitability ratio is only statistically significant in R, and expected negative signs are present in R and R. . Since beans are traditional crops and both traditional and commercial crops appear in the numerator, an inverse relationship between the ratio and the dependent variable is correct. For the same reasons, the positive sign in Rj. can be regarded as unexpected. Income-Quantity Relationships The income elasticities (Table 15) and the income-quantity relationships (Figure ] k) for beans show the traditional character of this enterprise. Beans present some income responsiveness at very low income levels, but as income increases the functions become almost perfectly inelastic as in R. and R above the Q50 level, and in R^ above the Ql 50 level. Farm Size-Quantity Relationships No farm size-quantity relationships are depicted for beans since comparisons are not possible because only one correct sign is present. Farm size elasticities for R_ illustrate very little responsiveness (Table 17). Unitary elasticity is found at the 0.25 hectare farm size level and thereafter, elasticities decrease sharply. At that point, other crops may enter the production system.

PAGE 137

119 Price-Quantity Relationships Price elasticities of market supply (Table 18) for beans are discussed without a graphical presentation because the price signs are negative in all three equations. The unexpected price sign can be explained as in the case of corn. A v;ide price range for beans prices, possessing the highest prices of all basic grains in the sample, strongly corroborates the reasoning behind the conceptual model. Increasing prices during the marketing period up to the asymptotic section of the PIC path may have resulted in marketed output reductions. Sorghum Sorghum is only grown as a single crop in R, . Regression coefficients (Table ]k and Table 15) and income, farm size, and price elasticities of market supply (Table 16 to Table 18) reveal a traditional crop with some degree of commercialization. Income, farm size, and price relationships are not depicted since no comparisons are possible. Regression Coefficients Total family income and quantity demanded on the farm conform to expectations regarding sign and level of statistical significance. Total farm size and price present neither the expected sign nor a level of significance. Education and distance, with minor statistical significance, carry unexpected signs. The relative profitability ratio presents the highest level of significance relative to the other

PAGE 138

120 variables in the sorghum equation and the correct sign; since sorghum is both a traditional and a commercial crop, with other crops of both types in the numerator, a direct relationship is expected. Income-Quantity Relationships Income elasticities (Table 16) reveal that sorghum is a very income responsive crop at low income levels, with the responsiveness decreasing as income increases. Since sorghum in this region is mostly sold to livestock feed processors, becoming a highly commercial crop, the elastic portion of the curves, located at very low levels of income, may reveal that farmers with low income levels are the main suppl iers. Farm Size-Quantity Relationships The total farm size coefficient presents an unexpected sign, a condition possibly related to the income responsiveness situation. If farmers at low income levels are the main suppliers to feed processors in the region, it is natural that, as the size of the farm and income increase, there is a tendency to reduce production thereby providing a basis for the indirect relationship between farm size and market supply. Price-Quantity Relationships The likely presence of traditional and commercial farmers in the sample may have produced the unexpected price sign. The limited number of observations for low quantities at high price levels might have caused the discrepancy by making the function slope in the opposite d i rect ion .

PAGE 139

121 Rice This basic grain is cultivated mainly in R,, R , and R,.. The regression coefficients (Table 14 and Table 15), the income, farm size, and price elasticities of market supply (Table 16 to Table 18), and the income-quantity (Figure 15) and farm size-quantity relationships (Figure 16) give strong support to the conceptual model of traditional and commercial supply response. In the case of rice, the land constraint plays an important role in shaping the appropriate characteristics for the crop. Regression Coefficients All coefficients of total family income and quantity of rice demanded on the farm present the expected sign and high levels of statistical significance. Total farm size shows the expected sign in R and R,, and is statistically significant only in R^.. The price coefficient is statistically significant in R. and R , with unexpected signs, and is not significant in R/. where It carries the expected sign. Education shows the expected positive sign in all three equations but is not statistically significant in R . Distance to the market for rice producers carries positive signs in R^. and R^ and a negative sign in R, while statistical significance varies from none in R^ and low in R^ to high in R,. The relative profitability ratio for rice shows more statistical significance in R, than in R^ and none in R . Positive signs in R, and R^ are expected. Since this is a commercial crop vnth subsistence crops in the numerator of the ratio, a direct relationship is normal.

PAGE 140

122 CTl OO ID (D E 0) (U vO to

PAGE 141

123 o o LA o

PAGE 142

\zk V/ith self-sufficiency secured, farmers can move into commercial -crop production. Having the same characteristics in R^, the ratio presents a negative and unexpected sign. Income-Quantity Relationships Appearing when basic Income levels have been attained, rice shows some income repsonsiveness at low income levels with the response decreasing less rapidly than for traditional crops. This behavior is substantiated by the income elasticities of market supply (Table 16) and the income-quantity relationships (Figure 15)The former characteristics follow exactly the description of commercial crops in the conceptual model. Low levels of home use further accentuate the commercial nature of rice in the three regions. Farm Size-Quantity Relationships The farm size elasticities for rice (Table 17) and the farm sizequantity relationships (Figure 16) strongly support the reasoning behind che theoretical presentation of chapter three. They also emphasize the major enterprise differences prevailing among regions, sub-regions, and even departments in Guatemala. Rice is, no doubt, a highly commercial crop in R^.. Cultivated mainly in the Zacapa area, where land is available, the rice relationship displays the shape of a commercial crop, supported by a relatively wide range in the elastic response and a minor amount (3 percent) of total production for home use. In R^, however, rice is grown primarily in the Jutiapa area by taking advantage of small pockets of suitable

PAGE 143

125 soil. Once those pockets are under production, enlargement of the farm will not influence rice production, or in other v;ords, the rice land constraint has been reached. For those reasons, farm size-quantity relationships for rice assume the shape of a commercial crop in R and of a traditional crop in R^ . The unexpected sign found for the farm size and rice supply relationship in R, can also be explained in terms of the land constraint. In the conceptual model, it was said that, as income rises, with selfsufficiency guaranteed, farmers tend to diversify production by growing high value crops until the land constraint is reached. In R, , besides the basic grains under consideration, plantain, sesame, and coffee are also present. These crops may offer farmers a better alternative as farm size becomes larger and cause rice production to vary inversely with farm size. Price-Quantity Relationships Price elasticities of supply for rice (Table 18) are discussed without the illustration of price-quantity relationships. The presence of only one expected sign eliminates comparisons among the three regions. Rice production in R^ shows the typical farmer response moving gradually up and along the PIC path as presented In chapter three. R, and R , however, reveal the same negative relationships encountered for several! other crops. In this case, higher prices with low quantities near the asymptotic portion of the PIC path are explained by the limited

PAGE 144

26 surplus available just prior to planting time when rice seed prices soar tremendously. By this time, farmers ^cannot, react strongly to high prices since they have been moving upward along the PIC path during the year. Wheat Wheat is produced and marketed in R, and R^. Regression coefficients (Table \h and Table 15), income, farm size, and price elasticities (Table 16 to Table 18), and farm size-quantity relationships (Figure 17) reveal a commercial crop whose behavior, heavily influenced by the governmental price support program, is contrasting in both regions. Regression Coefficients While total family income for wheat presents the expected sign and the highest level of statistical significance in R, , it shows neither characteristic In R,. Total farm size displays the expected sign In both equations but is more statistically significant In R. than In R,. Quantity demanded on the farm, with the highest level of statistical significance, presents the expected sign in both regions. Price carries the expected sign in R, and R^ but is of lower statistical significance in the former than in the latter. Education, being more statistically significant in R, than In R,, carries an unexpected sign on the latter. Distance to the market relative to wheat supply shows a positive sign in R and a negative sign In R^ and no level of statistical significance In either.

PAGE 145

127 o o CM fO o

PAGE 146

128 The relative profitability ratio presents high levels of statistical significance and the expected signs in both wheat producing regions. The positive sign in R, implies that as the ratio (return per hectare in all crops except wheat divided by the return per hectare in wheat) increases, the surplus-output ratio is expected to increase. The numerator in this case includes some subsistence crops while wheat in the denominator is commercial. Having secured self-sufficiency, farmers can afford to grow commercial crops where risk is minimal as is the case of wheat. This case illustrates the typical subsistence region described in the conceptual model. The negative sign in R^ is as expected since there are traditional and commercial crops in the numerator of the ratio. Rice, for example, may well be a better alternative than wheat in a region as commercial as R^. Income-Quantity Relationships The traditional nature of R, as opposed to more commercialized wheat production in R-. is very well documented by the income elasticities of market supply (Table 16). V/heat is a commercial crop in both regions. However, wheat supply does present very little income responsiveness in R, and the opposite sign in R^. in support of the conceptual model, traditional farmers in R. , once self-sufficiency has been secured, grow a little wheat which provides a relatively secure source of income. The weak income responsiveness may be caused by the price support program. Although no quantity restrictions have been imposed, the price support is also a ceiling price and may be viewed as a limit on producer revenues

PAGE 147

129 beyond v;hich higher value crops may become a better alternative. Because more commercialized regions display a stronger tendency to move Into higher value crops, R, carries a negative sign for the income variable. Farm Size-Quantity Relationships Farm size elasticities (Table 17) and farm size-quantity relationships (Figure 17) further support the statements of the former section. In both regions, the elastic response is minimal up to the 0.25 hectare size, beyond which the responsiveness decreases sharply. Besides the reasons explained above, this reaction could be the result of the heavy use of chemical inputs discussed in chapter four. Intensive application levels and consequent yield increases may be the same as devoting more land to wheat production when land becomes avilable through the use of new technology. Price-Quantity Relationships Price-elasticities of market supply (Table 18) reveal that wheat production is minimally responsive to price changes. Wheat producers probably behave in this manner as a result of the price support program. Summary An analysis of the traditional and commercial supply response by producers of basic grains was accomplished by estimating and studying the regression coefficients and the respective elasticities for basic

PAGE 148

130 grains in five regions of Guatemala. Explanations for the behavioral characteristics identified provide support for the theory as expressed in an ear 1 ier chapter . Careful attention, however, must be given to generalizations based on these results. The following chapter will pursue the general implications of the descriptive and regression analyses .

PAGE 149

CHAPTER VI SUMMARY, CONCLUSIONS, IMPLICATIONS AND RECOMMENDATIONS This chapter contains a brief description of why a study of traditional and commercial farm supply response was undertaken, and the objectives necessary to adequately investigate the problem related thereto for Guatemala. Research findings and their implications are presented. Without a thorough examination and presentation of these results, little will be gained in the quest for a better understanding of traditional and commercial supply response. Thus, this chapter draws conclusions and proposes recommendations based upon the implications derived from the empirical results. A special section is devoted to discussing some data problems encountered in the research and how they may have affected the results. Problem and Objectives Characteristics portraying Guatemala as a developing country include: a rapily growing population, two-thirds of which is employed in the agricultural sector; a limited arable land base; and many farmers living in poverty conditions, with high rates of unemployment, and very low levels of food production. For these reasons, the country's 131

PAGE 150

132 development efforts are concentrated on the Implementation of programs designed to more intensively utilize land, to reduce unemployment, and to increase production and productivity in rural areas. V/ork at the institute of Agricultural Science and Technology ( I CTA) of Guatemala is focused on subsectoral programs intended to develop new technology. The quest for technology is aimed at generating productivity increases, especially in basic grains, to enable the country to meet its requirements without increasing the land area committed to production. Productivity advances, however, may create tv/o different problems. First, small farmers, discouraged by the erratic behavior and low level of basic grain prices, may utilize the new technology to produce the same amount of grains on less land and devote the unused as well as new land to the production of other crops. This has been observed recently in some areas of the country. Second, if farmers utilize the new technology on all of their land, the so called "second generation marketing problems" are likely to appear. Since it becomes important to understand the traditional and commercial farm supply response as a basis for policies focused on both of these problems, the main objective of this study was to estimate market supply functions for each basic grain or association in the different regions of Guatemala. Other objectives were to compute the corresponding income, farm size, and price elasticities of market supply and to delineate and quantify production-distribution activities for basic grains in the different regions of the country. A Small

PAGE 151

J33 Farmer Credit Survey conducted by the Government of Guatemala and the Agency for International Development (AID) in IS?'^ provided the data necessary to accomplish these objectives. In general, it was hypothesized that, income, farm size, and price elasticities of market supply for both traditional and commercial basic grains are high at very low levels of income, farm size, and price, respectively. But at higher income, farm size, and price levels they tend to become almost completely inelastic for traditional crops but somewhat less inelastic for commercial crops. To test these hypotheses, market supply equations for each single crop and associated crop enterprise were estimatec separately in each region of the country. It was also hypothesized that if the productivity and production of basic grains can increase, production and distribution activities seem to be adequate. To test this hypothesis, production and distribution activities were delineated and quantified. The results obtained are summarized in the fol lowing isection. Research Findings Results found in the delineation and quantification of the production and distribution activities are discussed first followed by a summary of findings concerning traditional and commercial farm supply response.

PAGE 152

13^ Production and Distribution Activities From the input standpoint, basic grain production is most influenced by seed and fertilizer costs. While fertilizer use tends to be a generalized practice, with the level of application depending upon crops and regions, pesticides and soil additives are not commonly utilized. Seed management becomes dependent upon product sales, seed storage, and seed purchase decisions. Thus, variation does prevail in the percentage of total production set aside to be used as seed and animal feed and the percentage of seed which is purchased. Regarding labor, corn, rice, and wheat are the enterprises with the highest employment per hectare, followed by beans and the associations. Except for the latter, where employment per unit of land is very similar, all enterprises present different levels of employment by region. Total basic grain production differs among crops with respect to yields and product distribution. Average production per unit of land is very similar for each crop grown in different regions. However, when the crops of the associations are grown as single crops, yield decreases for beans while increasing for corn and sorghum. Excluding wheat and rice, consumption per family is relatively large and does not show major regional differences. Corn is the grain most used for processing, sales "In kind," and donations, all of which are not very generalized activities. Variations found In cash sales are the result of differences in farm demand for production and consumption purposes. The more traditional the crop is, the lower will be sales. Expenditures Incurred

PAGE 153

135 in marketing of basic grains are generally one cent or less per kilogram. When these expenditures are expressed as a percentage of the average regional price and ranked from highest to lowest, the order is wheat, rice, sorghum, corn, associations, and beans. Traditional and Commercial Farm Supply Response In general, estimated regression coefficients behave as hypothesized. Total income, total farm size, and quantity demanded on the farm are highly significant variables and, with few exceptions, show the expected sign. Price presents different levels of statistical significance and alternate signs. Education, distance, and the relative profitability ratio provide a minor contribution to the model. Traditional crops generally appear at near zero income levels while commercial crops are cultivated when higher levels of income have been attained. Income elasticities of market supply for both types of crops are very responsive at low income levels. However, while commercial crops still show some responsiveness at higher income levels, traditional crops become aliiost perfectly inelastic. These findings corroborate the theoretical presentation. That is, farmers at subsistence levels experiencing income increases devote new resources to production and react by marketing the newly created surplus. At higher income levels, responsiveness tends to decrease sharply for traditional crops; once the home use requirement is attained, commercial crops enter the production system. Traditional crops pervade the basic grains spectrum in Guatemalan agriculture. All of the enterprise associations, being the basic subsistence cropping pattern, belong in the traditional category. Corn is

PAGE 154

136 a traditional crop in R , R , and R^ , but becomes commercialized in R and R,. Beans are traditional in all regions. Sorghum is both a traditional and a commercial crop in R,Rice displays the characteristics of a commercial crop in all three regions (R, , R^., and R-.) where it appears. Wheat in R. is a commercial crop and is not highly income responsive since it serves the purpose of providing farmers with a relatively secure source of income at low income levels. At higher levels of income, crops other than wheat may become a better alternative. Although no quantity restrictions have been imposed, the price support, by establishing both a minimum and a maximum price, may be viewed as a ceiling on producer revenues. R^ supports the former explanation; being a highly commercialized region, as opposed to R. which is mainly a subsistence region, wheat presents the opposite income sign in R^. Other commercial crops may have become more income rewarding enterprises. Total farm size elasticities closely parallel the income elasticities and also support the conceptual model. Traditional crops appear at minimal farm sizes while commercial crops are grown as farm size increases. Both traditional and commercial crops are very responsive at low levels but while some farm size-supply responsiveness remains at higher levels for commercial crops, it decreases sharply for traditional crops once self-sufficiency is attained. Concerning farm size elasticities, all crops can be cateogrized in the same way as those for the income elasticities. The price elasticities of market supply are generally very low for both traditional and commercial crops. They show a higher response

PAGE 155

137 to low price levels than to higher prices. Since farmers move up and along the pr iceincome-consympt ion (PIC) path and the surplus decreases during the marketing period, they can not react strongly to price changes at the end of the season when prices are highest. The opposite signs found for price in many of the equations can also be explained in the same terms. Thus, it may be possible that, when prices are highest, farmers have already arrived at the asymptotic section of the PIC path and, therefore, higher prices will encounter a lower quantity marketed response. Data Generalizations and Implications Descriptive statistics and statistical inference are used in this study. Since the data come from a random sample and do not encompass the entire population, two main assumptions are necessary to make inferences from the statistical results to the population. First, it is assumed that the sample is representative of the true population and, second, that 1973 was a typical year. Both assumptions appear to be reasonable. As shown in chapter one, the sample contains a sufficient number of observations of traditional and commercial farms to draw safe conclusions at the regional and national levels. Concerning the second assumption there are no reasons to believe that 1973 was not a typical year. Furthermore, It also has been proven in the appendix that the least squares estimators of the regression coefficients are the best linear unbiased estimators (blue) of all linear unbiased estimators of the respective parameters.

PAGE 156

138 Notwithstanding the above qualifications, the data display sufficient characteristics conducive to errors in the interpretation of results to necessitate a discussion of these concerns before recommendations are made. Errors and Omissions in Data Recording Four errors in data recording related to the information used in this study can be identified [106]. The first, and a very important one, relates to lack of care by the interviewers in recording responses to the question that deals with interplanted crops. Emphasis was not given to recording which crops are interplanted and which of the interplanted crops is the principal crop [l06,p. 79]. This omission is mainly reflected in corn and beans in R, , R,., and R, . The second major datarecording error entails the distance variable where figures given in meters or fractions were rounded to the nearest kilometer [106, p. 68]. For that reason, all entries start at the one kilometer level. Third, not all physical losses were recorded, especially by farmers v;ho consume a relatively large share of their production [106, p. 11]. This error appears in the very unlikely 1 percent average computed for losses in all basic grains. Finally, interviewers were not consistent when recording production withheld by farmers for sale at future dates [106, p. 77]. This situation, however, does not affect the results obtained but it does support the theoretical model discussed in chapter three since the model is based on the assumption that farmers save some production to be sold throughout the marketing period.

PAGE 157

139 To the errors and omissions just mentioned, can be added a question in particular that was badly designed and other ommissions. When asking to whom production was sold, it was only possible to check one, two, three or any combination of alternatives but specific quantities sold to each outlet were not obtained. This failure makes it impossible to know the amount of basic grains going through the different marketing channels whenever more than one channel was checked. The remaining omissions relate to failures in specifying quantitative values for several variables such as education, distance to the market, and quantity demanded on the farm. A value equal to the mean was assigned to replace these missing values only when regressing the corresponding equations. Upward or Downward Bias Descriptive statistics for the variables included in each of the estimated equations are computed as a basis for discussing the introduction of possible bias in the results. Minimum and maximum values, mean, standard deviation, kurtosis, skewness, missing observations, and total number of questronrra'i res by region and crop are presented for each independent variable in Table A-1 through Table A-7. Kurtosis refers to the relative peakness or flatness of a curve. A value of zero indicates a normal distribution; a positive value means a narrow (more peak) curve, while a negative value indicates a flatter curve. For skewness, a zero value corresponds to a bell shaped distribution; a positive value indicates clustering to the left of the mean with most extremes values to the right, and a negative value means the opposite. The remaining statistics and values are selfexplanatory.

PAGE 158

lAO Education of household Head In general, the number of years of formal education is relatively low in every case (Table A-2) , Although the results obtained reveal normal distributions in almost every case, some consideration should be given to the occasionally large number of mi"s-s"i,ng observations . These observations were made equal to the mean when, in fact, failure to report educational level might have been due to situations of lower levels of education. The resulting small difference, however, should not greatly affect the results. Distance to the market Besides the error leading to the one kilometer starting point for all farms, there is no reason to believe that the results obtained for this variable are not representative (Table A-'t) . A relatively small number of missing observations does not present major problems of misleading data when set equal to the mean. Total Farm size Total farm size deserves special consideration. Since the main purpose of this study is to draw inferences about traditional and commercial farm supply response, size of farm becomes a good indicator of the extent to which the data represent farmers involved in either or both types of farming. Although size of farm has not been defined in the present study, both extremes of the spectrum are not adequately represented. Regression equations with a few relatively large farm sizes, however, were included (Table A-3) . The highest mean values.

PAGE 159

]k] between 15 and 2k hectares, are localized in the corn equation of R , In the rice, corn, and beans equations of R,., and in the beans and cornbeans equations of R . . However, the kurtosis and skewness statistics 6 computed reveal a positive sign for all the equations meaning both narrow distributions and clustering to the left of the means with most extreme values to the right of the mean, respectively. Thus the few relatively high values do not appear to impose bias in the results obtained. Their presence, however, is revealed and should be recognized when interpreting results for those enterprises. Total family income Similar in importance to total farm size, this variable also reveals in some of the equations, the presence of values higher than the nondefined total family income (Table A-7) • Although total family incomes of values higher than Q10,000 a year are found in several equations, mean values are relatively low in all equations. The presence of a positive sign in both kurtosis and skewness has the same implications here, meaning the apparent upward bias in the data in these cases in not creating difficulties. Farmgate price The price variable is important in the model. The values and statistics computed stimulate some concern about the degree of validity of the findings in several of the equations (Table A-1). All crops, except wheat in R,, present a relatively large price range to permit estimation of the equations. Standard deviations, on the other hand.

PAGE 160

142 are relatively lov/ to allow for estimation within comfortable limits of confidence in most of the equations. A zero or minus sign in kurtosis, signaling a normal or flatter distribution in prices is only present in six of the equations. Besides these six, another four equations diplay a sl
PAGE 161

143 not be replaced by mean values since it is incorrect to attribute unearned revenue to these farmers. Therefore, cases v/i th relatively high numbers of missing values are approached with caution when analyzing the results obtained. Conclusions and Recommendations The al ternat ive quest ions to which this study is addressed are as follows: Do traditional farmers adopt the new technology being generated by iCTA for basic grains to produce the same or less output on less land, or do they make full use of the land and technology to augment basic grain production? V/hat will be the consequences in each case? The argument in support of the national policy objective to increase basic grain production has been widely discussed in the development literature. The reasoning is that, in a closed economy, food grain prices would fall as a result of significant increases in production. However, lower prices could still provide adequate incentives to farmers if much of the increase is to due to cost-free technological change. Furthermore, with substantial supplies of grain, the government can have much more expansionary fiscal and monetary policies which, if directed toward labor-intensive public projects, can shift the demand curve for grains, and thereby help to counteract some of the decline in prices [32, p. 70^]. In the case of Guatemala, demand elasticities for basic grains are not known at any level of the marketing chain. Empjrical studies conducted in similar countries have produced inelastic demands. However, the impossibility of estimating demand elasticities at the farm level in this study gives rise to some concern. The problem seems to revolve

PAGE 162

Uif around the question of whether or not self-sufficiency has been attained in certain regions of the country. Quantities marketed will therefore vary accordingly since the magnitude of the elasticities will differ in every case. Demand elasticities at the consumer level cause less concern. In general, the country is a net importer of basic grains and the demand curve for these grains is elastic at the imported price; an increase in production would probably not drive prices down but would instead bring beneficial effects to the economy. Since the world demand for most basic grains is also elastic at the market price, the country could export any available surplus not absorbed by the domestic market. The question is solved therefore except for the unknown elasticities of demand at the farm level and for the presence or lack of adequate facilities to market the increased production. The remaining question is more complex. It has been shown that income, total farm size, and price elasticities of market supply are relatively high at low levels with the responsiveness decreasing at a rapid rate for the subsistence crops and at a lower rate for the commercial crops. Wheat, however, is an exception. At higher income levels, the response functions become almost perfectly inelastic. Therefore, it would appear that little hope prevails for the attainment of massive increases in production of all basic grains. Some basic grains in some regions seem to have a slight potential for increased production. These are corn in R_ and R,, and rice in R, and R^.. But, in general, the resulting increases would fall far behind the desired goal and expectations of the Guatemalan government.

PAGE 163

H5 Another relevant finding is an indication that traditional farmers shift to commercial or high val ue crops once self-sufficiency has been reached. Such shifting may cause serious repercussions. Marketing facility needs for high value crops are in general more sophisticated than for basic grains. These products display more possibilities for damage, spoilage and price differences than basic grains. Therefore, more sophisticated grades and standards, and transportation, handling, packing, storage, and market information facilities are needed. The above conclusions serve as a base for several recommendations: First, seasonal demand studies at the farm and consumer levels are necessary not only for basic grains but also for high value crops. This would ease the quest for information about the prevailing and future trends in conditions of demand and supply and thereby provide a basis for developing a cropping pattern that would not distort the market mechanism. Second, basic grain production should be emphasized in the crops and regions presenting the higher probability of increasing production. By concentrating efforts in the specific crops and regions where such increases are most likely, (corn in R and R, , and rice in R. and R-) , greater accomplishment may be expected. Finally, it has been Inferred that, for the Guatemalan situation, basic and applied research on basic grains alone will neither serve the small farmer's needs entirely as he moves into higher value-higher risk crops nor will it serve the national production goals for basic grain. Furthermore, there seems to be a contradiction between the objective of increasing basic grain production and the goal of overall development of the country. If increases in average per capita income can not be

PAGE 164

U6 obtained for small farmers alone from the production of basic grains, even if production targets are met, the goal of increased production of basic grains contributes little to economic growth since the traditional farm sector is the one most needing increases in income per capita. Thus, besides production research, careful consideration should be given to various other alternative programs as incentive to stimulating production to meet national goals while fulfilling the risk aversion and income criteria of traditional farmers. Because of the somewhat diverging yet complementary behavior of traditional and commercial crops on Guatemalan farms, research emphasis must also be assigned to high risk crops along with basic crops. This research must assume a farm system focus while avoiding isolated enterprise evaluations if it is to be of use to small farmers and to meet the production goals of the national government.

PAGE 165

CHAPTER VI I REFLECTIONS ON THE THEORY OF DEVELOPMENT Introduction ....What we tend to forget, however, is that the essential aspect of an 'underdeveloped' economy and the factor the absence of which keeps it 'underdeveloped' is the ability to organize economic efforts and energies, bring together resources, wants, and capacities, and so to convert a selflimiting Stat ic system into creative, self-generating organic growth [28, p. 335]. However, when the efforts are organized in reverse and the energies and tasks are working toward unattainable goals, the limitations will perpetuate themselves and the self-generating organic growth will never mater ial ize. It is a reality that all developing countries, at some stage in the development process, must face the issue of extracting a surplus from agriculture while at the same time providing for public investments in the agricultural and industrial sectors. But careful attention must be given to fomenting the realization of a surplus where it is a real, not imagined, possibility v;ithin limited resource conditions. A serious misjudgement can lead to a waste of time and resources that might be used IV

PAGE 166

U8 more effectively. The opportunity cost for developing countries in this case is extremely high. The review of literature in chapter two reveals a theory of agricultural development constantly evolving since the end of World War II. That the agricultural sector is to play a key role in the development process is today widely accepted. The precise nature of this role and policies most appropriate to fulfill that role, whatever it is, are not fully agreed upon. One of the prescriptions most often followed has been to emphasize increasing production of food crops per land and labor unit by relying on modern yieldincreas ing technology. Yet both productivity increases and stagnant or e.v_en decl i nlng production have been observed in some of these countries. The reason for the disappointing results is the failure to analyze the total small farm or traditional basic economic system. This study has attempted to close that gap in the theory. Chapter three has presented a conceptual model of the t.oJ:;a.l basic economic system for "traditional" or "small" farms. Owing to his subsistence needs, the land constraint, and his income level, the traditional farmer's behavior within his basic economic system is one of carefully balanced risk aversion, income ma intenance,and risk taking. The results presented in chapters four and five tend to validate the model. With the corresponding adaptations the model can be useful for the analysis of the traditional farm sector in different countries with varied single and associated cropping patterns. The results of the model are now merged with the three generation problems of the Green Revolution.

PAGE 167

]kS The Green Revolution: Generation Problems and Small Farm Development Three generation problems related to Green Revolution agriculture have been explicitly delineated by Walter P. Falcon [32]. Research findings from the present study in Guatemala further expand and to some extent modify the implications of these problems. First Generation Production related problems, where great production successes have been hampered by serious limitations, are included in the first group. Constraints on adoption of new technology include, for example, lack of adequate and controllable water supplies (without irrigation, fertilizer provides only a low return) and inadequacy or lack of pest management programs. Regional differences in some countries may illustrate two fold yield increases per acre in one-third of the country due to new technology yet no change elsewhere within the same country [32, p. 701]. Reasons for thi s cond i t ion are in part explained by the Guatemalan experience. Farmers tend to adopt new technologies as risk is reduced and when clear income advantages appear . They are not likely to incur more risk until at least self-sufficiency is established. Thus, risk reduction can occur within the present self-sufficiency crop and income patterns and/or in a potential crop addition to that pattern. Both types of risk reduction may create similar impacts on production systems changes implemented by traditional farmers.

PAGE 168

150 This explanation of traditional farm behavior is corroborated by Figure 18 where traditional and commercial farm income, total farm size, and price-quantity relationships found in the basic grain supply response for Guatemala have been depicted. The supply responsiveness to changes in income, farm size, and price (being larger for traditional crops than for commercial crops at low income, farm size, and price levels, but decreasing faster for the former than for the latter at higher income, farm size, and price levels) has given support to the conceptual model of this study. In addition, the positions of the intercepts for the different crops, by being lower for the traditional than for the commercial crops, further validate the conceptual model. Because of the different and complementary behavior with both types of crops, research emphasis must also fall on high risk crops and not just on basic crops. In a recent study about rates of adoption of modern inputs in several developing countries, the authors recognize that "experimentation with new techniques involves the risks of the unknown, usually involving additional investment, and small farmers may be less able to undertake such risks" [96, p. 888]. This finding is related to the traditional farmers' behavior, explained in the present study, with regard to higher risk crops. Even in the case of known varieties, traditional farmers will not be willing to take any risk until they have attained individually required self sustaining income levels. Off-farm and part-time rural employment along with agricultural productivity advances in basic crops can provide this stimulus.

PAGE 169

151 Quant i ty Figure 1 8.--Tradi t ional and commercial income, farm size, and price-quantity relationships in developing agr icul ture

PAGE 170

152 Second Generation Second generation problems encompass difficulties associated with marketing, markets, and resource allocation. Examples of marketing and demand problems generated by the Green Revolution are: transportation bottlenecks; differences in milling, grading, storing, and transporting the products; low consumer acceptance because of quality problems; pricing and marketing inefficiencies; and, finally, barriers to entering international markets. Falcon [32, p. 701] acknowledges that, even v/ith moderately high on-farm demand from increased production, quantities marketed have risen much more than proportionately to quantities produced. In chapter six, it was recommended that demand studies at the different levels of the marketing chain be conducted. Most marketing problems can be reduced with policies and programs based on knowledge of the on-farm elasticities of demand and the proportion of the increased output the remainder of the population is willing to absorb at prices commensurate with production costs. On the other hand, if production remains stable while productivity for a basic grain increases, the market for the basic grain probably will not receive pressure and falling prices will not result. To achieve increased productivity, stress may be placed on input market systems. But possibly more important is the potential pressure on the market for higher risk commercial crops since farmers may shift to producing these crops after productivity increases have been obtained in the traditional crops. Risk associated with those commercial crops in

PAGE 171

153 part can be reduced by placing emphasis on improving market conditions and prices for those crops. Furthermore, input market pressure also may be placed on some non-traditional inputs but not exclusively those necessary to service traditional basic crops. Third Generation Receiving the least attention, third generation problems encompass equity, welfare, employment, and social institutions. They arise from four principal sources: First, annual population growth rates of over 2.5 percent in areas already densely populated; second, very low average income levels, coupled simultaneously with great regional and personal disparities in income, wealth, and political power; third, limited opportunities for off-farm employment; and finally, the possibility for technological "leap-frogging" with agricultural inputs and techniques, which are often of a labor-displacing nature. A built-in supply control mechanism for basic grains and low valuelow risk crops produced by the small farm system has been suggested in the conceptual model. Because of that mechanism, over production, at least at the small farm level, might not result so prices should not decline sharply to create great income disparities. On the other hand, if in order to obtain the desired total production increase at the national level emphasis is placed on some commercial basic gain production under larger farms, small farmers will be affected by the fall in basic grain prices. But if the emphasis is maintained on increased basic grain production by the traditional sector, the government will be enforcing

PAGE 172

15^4 contradictory policies. That is, a conflict prevails between the production goal, which would not substantially increase average per capita income of traditional farmers, and the goal of economic development for the country. Traditional farmers, however, apparently may not be counted upon to substantially increase total production of basic grains to meet the national goal. Yet since they do contribute toward that goal, research on basic grains for traditional farmers is still necessary so that they can realize the productivity increases that will provide the opportunity for them to produce higher value crops. If commercial basic grain prices fall as a result of increased productivity and production, traditional farmers may be forced back into greater land use for basic grain production to secure their low risk low money requirements; therefore, research must continue to provide for increases in traditional basic grain productivity if balanced growth is to occur within the agricultural sector. Employment related problems are an integral part of the role of agriculture In economic development. Today it appears that the need is not to send rural people to the cities (an old theory to provide cheap labor) but to employ migrants and potentially displaced small farmers on farms as a means to reducing unemployment and income distribution problems. Rural small industry may serve a double purpose for the food system by providing needed employment as well as preprocessing, processing, packing, and storage for some of the surplus production. Working part-time off the farm does not imply a decline in on-farm productive activities. It has been shown in the Guatemalan situation, that, when husbands take up a part-time job, either In the

PAGE 173

155 cities or in the country side, wives remain in charge of agricultural activities. The added family income and security related thereto may provide a basis for moving into higher value-higher risk crops just as traditional crops provide that basis. Suggestions for Further Research Having to depend entirely on data collected for a purpose different than the estimation of the model portrayed in this sutdy has placed some undeniable limitations on the scope of the research and results. The most limiting condition has been the impossibility of testing for the presence of a backward bending supply curve for basic grains. It was indicated in the conceptual model that, as income and farm size increase and small farmers move out of subsistence into commercial agriculture, there is a tendency to cut back on production of traditional crops. The reciprocal form specified for these variables, due to the nature of the data, impeded the functions from bending backwards. In the case of price, the unexpected signs obtained may also signal the possibility of a backward sloping supply curve as the result of a limited surplus available at the end of the season, when prices are high. Another reason might be the income effect as the farmer moves up and along the priceincome-consumption path to a higher income level. In the following season, the farmer moves into commercial crop production and devotes less land to traditional crops. Further research should test for the possible presence of that supply curve. For such tests, countries and regions should be carefully selected to include those with desired yet typical characteristics. Questionnaires should be designed to collect the necessary and appropriate data.

PAGE 174

156 which would of course include sufficient observations of the high-value and high risk crops. That research, when accomplished, will contribute to a better understanding of the small farm basic economic system in the developing nations. Epi log Despite the considerable attention given to the modernization of traditional agriculture during the past quarter century, the small farm sector has not received sufficent attention. "It Is Imperative that this mass of humanity," as pointed out In a recent publication [Sh , p. i], "be included In the modernization process and share in the material and other benefits of economic development and social progress." The reasons are fairly simple: The state of the arts and the knowledge base in this area are dangerously Inadequate. Development theory treats the problem of this important stratum of the rural sector inadequately. Much of the empirical work has abstracted from these problems. Many development projects have failed to achieve desirable impacts on the rural poor. Information relative to the fundamental characteristics of this stratum and the barriers which it faces is sparse. The agricultural development spotlight is now beginning to focus on the basic issue the unmitigated poverty of disenfranchised rural inhabitants. Development efforts have no. alternative but to tackle this massive problem. To do so effectively will require sharp expansion of the relevant knowledge base. It will necessitate modification of conceptual models, expansion of empirical information and the creation of effective development strategies and programs, [9A, p. I]. That concern has been present throughout this study. Recent developments in the literature seem to indicate that the time has already

PAGE 175

157 come for proper priority to be given to small farm agricultural development within the general economic development framework. The results, when incorporated within effective development strategies and programs, will help resolve one of the most crucial problems faced by developing countries today.

PAGE 176

glossary' Aldea: Hamlet or small village. Associated enterprises: Sequential intercropping of two or more crops such that all production practices refer to the entire combination of the crops included. Cabecera: Capital of a department or mun ici pio . Canton: A territorial subdivision roughly equivalent to a country, if rural, or a ward, if urban. CaserTo: Rural community too small to be considered an al dea . Often only a collection of scattered dwellings. Ciudad: City. Departamento: Each of the 22 major political subdivisions in which the Republic is divided. ICTA: Instituto de Ciencia y TecnologTa AgrTcolas (institute of Agricultural Science and Technology). Decentralized institute of the Governmental Agricultural Sector inaugurated on June 1, 1973, with the purpose of conducting research to generate new technologies mainly for medium and small farmers. INDECA: Instituto Nacional de Comercial izacion AgrTcola (National Institute of Agricultural Marketing). A decentralized agency in charge of all agricultural marketing activities in the country . Ladino: According to the IBS') Official Census, term applied to anyone who was not a cultural Indian, which includes persons of European and Asiatic heritage as well as acculturated Indians. Manzana: A unit of land equal to SSSk.h square meters. Milpa: Corn, most of the t im e intercropped with beans and/or other products . This section is mostly based on [2't] 158

PAGE 177

159 Municipio: Political subdivision of a department. Similar to a township in the United States. Pueblo: V i 1 lage. Quetzal: Unit of currency, equivalent to one U.S. dollar. Also the national bird of Guatemala. Quintal: A unit of weight equal to 100 pounds, or hS,},53 kilos. Villa: Small town, larger than a pueblo.

PAGE 178

APPENDIX

PAGE 179

APPENDIX The primary purpose of this study has been the estimation of market supply functions for basic grains in the different regions of Guatemala. This appendix contains the list of crops involved, a complete specification of the mathematical and statistical models, and the regression results. List of Crops Basic grains include corn, beans, sorghum, rice, and wheat. They may be grown as single crops or associated with one or more crops. The regional distribution of crops for which equations are estimated is as follows: For the associations, corn-beans (C-B) in R, , R_, and R^; corn-sorghum (C-S) in R, ; and corn-beans-sorghum I !? b b (C-B-S) in R,; corn in R. , R , R , , R , and R^; beans (B) in R. , R , and R^; sorghum (S) in R, only; rice (R) in R, , R , and R,; and, finally, wheat (W) in R, and R. . I b The Mathematical Model The theoretical model developed in chapter three provides the basis for the estimation of the surplus-output ration as a function of a number of independent variables. Variables in the equation are: 161

PAGE 180

162 M T Q. / Q. = quantity marketed divided by quantity produced of basic grain i; or percent of basic grain i that is marketed (thie dependent variable); P. = farm price of basic grain i (quetzales/kg) ; E. = education of household head (number of year of formal education): A. = total farm size (ha); D. = distance to the nearest market (km); I. = quantity of basic grain i demanded at the farm level for all purposes (kg); W. = return per hectare in all basic grains except basic grain i divided by return per hectare in basic grain i (quetzales/kg/ha) ; and Y. = total annual family income (quetzales). Descriptive statistics for each of the independent variables appear in Table A-1 to Table A-?Their implications have been discussed in chapter six. Before stating the mathematical form of the behavioral equation to be estimated, some assumptions regarding the behavior pattern of the independent variables must be made. It is assumed that education (E.), distance (D.), quantity demanded on the farm (!.), and the relative profitability ratio (W.) enter the equation in direct form. It is further assumed that, based on the conceptual model, price (P.), total family income (Y.), and total farm size (A.) enter the equation in M reciprocal form. Since quantity marketed (Q.) is the only endogenous variable, the model can be solved with the following single equation:

PAGE 181

163 1/1 in QJ c 3 to v£)r^oor~-~' — ooLnr^ooocMP^ — — -=r — o -— -o o o O^OCNJcslfslO^-CM'-^OO'— t I I II in O 4-" 13 oa-dLAO' :r — r^cou^oLr\cr\ocv~iocvj I — I o I • > i-i (U I/) Q r^csjooo-d-vD-3-o-3-i^^-;rcn' — oD-a-oov^\X)cNj cs •Lin 0) tn in — XI s: o ooooooooooooooooooo X LAsO' — vDvDc^r^-OCMLA. — — O — 0~\r — vOCMLA c<^o r^r^cv-», 3r^ooMO — ctvlacm — oooooooo CMCAtN' — CMCM — ' — OAcMr~~-3-r~.CNI-3-CMr«-»CM'— ooooooooooooooooooo LACMLALALACMCM— 00-3-vDr^Ovnr-.rAOLACr\ COr^i — LAOLA 3-CMLA' — CA. — viSf^CM — O^CM OO — O' — OOOOO' — O' — OOO' — o — OOOOOOOOOOOOOOOOOOO CO D. I O m QQ CO CO CQ I I I I I
PAGE 182

le** .c O n 0) 4-> E tn JZ u 0) M Ul 0) > u I/I 0) •a 0) > c o ro U 3 M .— u in 0) Ul {/) — JH z: o X CL o c o en 0) a: vDO-d-' 3-oo^r^cMC7-\oDorocr\cncNjcx5a~\cr\ OOOOOOOOCN — 00--00^0ro — r^roocnocNi-T. — rooocoLA. — r^ocTvLncTir — — o I I o ^ I I O O O VO CM I OOOO— OCM— LAO I 11 — O — -3-— vDOO-3-v^CNCMr--.LrvOLA-3-vOLaoOtNI COoAO-^vO^DvOrAOOOU-\-3-CO— MDOOvOCArA cA-3-csoAr-~vr>cNjcNvovoovD-3-' — vr)Ov^oo OACTV^O LTivDJ~(T\ • — rACO-:r CACTiOO O rA-d" Csl rocNi cACAOArAcAcN-a" rAcsj cArAcM cMvO-drAcA rACAlAOOvjDvD. — OOO — ' — rA-a-CNJCSJOOD-:rLrv vOcA-d-rA — oOLAOLA-a-cNivDcNj-a-uni-ncNjocNi (N CM — • — CVJ cNi LAcAcAi-^ocovDvo cAMD-a" r~^o O CM-cr CnLA -3". — . — fvj PA. — a O \0 CSILACNIOACA. — C^. — -^ 'PA. — OOvO CSILACNIOACA vDvD crv>~DvD CTiv^ I — CO — vDvD — sOv^OO\CC0v£) _ — —

PAGE 183

165 01 c O cr 0.1 a o 1_ O o 4-1 U1 0) > 1_ U XI JQ TO 1_ to > N l/l E i_ 4-> O I I I < -Q l/l yi 0) c 3 CO vOr^OOt^MDOCMI^^rOvOLAvDLnoOO^^OOr^ cr\r--LA-3--a-oovO o cr>r^o o-cr crwo o^cnvo — — c^ CSl CM CMCNICNMDLA.— Lr\-31_ • > CO Q c (U en

PAGE 184

166 in c o TO cr 0) o V *j (/I tt) 0) u TO G) O O ro -t-j in > o If) D XI ro ro > (U L. ro E 0) o c ro in O D ii • > CO Q C ro CD • c > — U in 0) — XI 2: o ro CL O c o en (U or vooovocNiv^vi)-a-oooLA — -a-' — • — r^cNjcsicn — r^cN r^cNi r-~.vD a-\ '\o 0-3--JcriLni-r\oo-^ r^r^ -3"' — c^' — ' — rv-\ocNj-3-cNicsl I -:3— CM csj o ro O — _ _ I CO ro O ro CPv O O vC I — o I r-^vD-a--^-— cr\v^ — ro-3-00-:l-CNiC»v^OOrO\^0 i^— o — cx)o~»vDr^oor^o<~ocri— t^v£) — — cr\ -:r — CnoCvDLO. — OcslOvDO^COCNJror~~roOvD , — — CMCSlCSJi — . — Csl — CMCM. — CM COLr\^-LAr-^CMvDOO-3-vOCM^OOOrOO I — ^oor^^cMLA. — rOCOrOOCOOCNl-3"' — O 00 o rsisDr^ocx3-TcM — o — — a-co-crLALncNic» . — CM — — CNJCM— <— CSJ' — .— .— CM' — — rOOOLAOOvDvO. — coo — ' — rO-d-cNCMOCO-cruO \£>r0-a-00 — COLOOLO-^CM^OCM-a-LALOCNJCDCNI CN CM — — CNl -3O
PAGE 185

167 a ro E 0) u (D 0) O W U 4-) (A 0) > o T3 (D E ID ID a 0) TJ C (D E 0) T3 i-l

PAGE 186

168 sz o in U TO +-> I/) > Q. 1_ O in fa i_ > m 1J3

PAGE 187

169 c o m cr E 1/1 o TO 0) u O U1 O TO I/) 0) > 1_ u 0) o TO TO > (U E O o c TO o I TO t/1 1/1 .cocncNiLncri-3-cM-a-ooc^or~^cNjr^ CNCNlf^CM — CSJ-T-:3-^^LncM LO urv . 3. qfv^ o •t-l • > CO Q c TO vOrv^n^OOoavD r^<— is\ — coc^u-vvo-a> — — — rv-\r — rr\ cvicN . — cvj — c > — i_ 01 (L) 01 i/l — Xi X O X TO Q. O o c o en ca-3" CTVvD rOLnO UrvvilvD LTVOO C7\0 CNIOO cr>vo CO\DvO\£) O csl Lnr^vOviDvJD caODvOOOvO OOOvO oo LAunro. — cncr\LAr»-\-3o^, — o pooo cnr^Lrvo 0-:r C7^0~\r^O-T-3r^vO Ln-3-OO LAvD CM ravD — cr\^TOi-Ar^oor^ov£)vorooocsicr\r-^rovDr-^ • — CM. — — . — CMCMCM— — r— r^csiroca C^ cr\ lr\ CO \0 \£3 • — CX30. — — f^-^CNCMOOO-^LA MDcv-\-:3-r^. — C0LAOLA-a-c\J\£)Cs|-:runLrvcSOCsl CM csl — — CM OOOOOOOOOOOOOOOOOOO OLAoovOO. — urvrAOur\r^»l^Lr\cv->ooLr\. — co vDvOcsJCMLACr\COCMOCMOvi)CN)CM-3-OCX)CnvD CTir^' — UTvcMCKIviO rOvD 000-:JO oAOMD CAOOvD r^r^cAcxD-ar-^covo r^CTicN Lacr>v£> cm p^-3r^t^ — — CA-3-CM CMf>0. :T — l~^OCX30000i-r\Of^. — OrAfv-\0 oco LnLALAcv-icAcn-^vo oatrvvo to I 03 CQ CD OCQCQCDl/)Q:c^0t:;3 r^ vo o

PAGE 188

170 Q. / Q. = 3o B 1 + BE. B, 1 + B, D. B^ I . + B, W. B^ 1 Setting the direct variables equal to their means, the following expression is obtained: M T Q. / Q. = Z B_i_, where X is one of the three variables (Y., A., P.) ' ' X III estimated in reciprocal form and Z is the intercept value with all variables other than X at their means. M T From the theoretical presentation, Q. / Q. should steadily approach nearer and nearer to the value one, without ever attaining this value. The magnitude of the response depends on the traditional or commercial character of the crop. In terms of limits, lim Q*!* / qT = lim (Z £i_) ' ' X = Z 1 im gi X-XJO =Z where < Z <^ 1 .0. The mathematical properties of the function can be illustrated with the following computations. Let us assume, for simplicity, that Y = 1 £ . X Then, when a = 1, and X takes on values of 1, 10, 100, ... , Y equals 0, 0.9, 0.99, ... ; and when a = 10, and X takes on values of 10, 100, 1,000, ... , Y equals 0, 0.9, 0.99 ... (Figure A-l)Each functionapproaches the value one with a different slope depending on the value of X, while their intercepts depend on the value of a.

PAGE 189

171 Figure A-I . --Mathemat ical properties of the specified function

PAGE 190

172 The Statistical Model: Its Assumptions and Possible Violations The specification of the linear regression model includes the regression equation and the basic assumptions. This section contains the full specification of the model and discusses possible violations of the basic assumptions. The Regression Model The multiple regression model is formally described as R Y. = a +.E, BX, + G. , I 1 = 11 I where Y is called the "dependent variable", X the "independent (or explanatory) variables", e the "stochastic disturbance", a and 3 the unknown "regression parameters", and the subscript i refers to the ith observation [65, p. 201]. The basic assumptions of the cross-section model are: (a) Normality: e. is normally distributed, (b) Zero mean: E(£.) = Oj 2 2 (c) Homoskedast ici ty : E(e.) = d , (d) The number of observations exceeds the number of coefficients to be estimated, and (e) No exact linear relation exists between any of the explanatory variables [65, p. 202, 3^8].

PAGE 191

173 Possible Violations of the Assumptions The main purpose of the model is to estimate the regression parameters by means of the assumptions underlying the model. It may be possible, however, that, in so doing, one or more of the basic assumptions may not be fulfilled. The purpose of this section is to explore the possibility that this condition has in fact occurred in this study. All assumptions are scrutinized to show that the least squares estimators of the regression parameters have all of the desirable properties. Normal i ty . --When the assumption of normality is not fulfilled, the least squares estimators of the regression coefficients are still the best linear unbiased estimators (BLUE), since this property is independent of the form of the parent population. They are therefore still unbiased and have the smal 1 est variance among all linear unbiased estimators of the respective parameters. Though they are no longer efficient, they can be considered consistent and asymptotically efficient. One practical implication of dropping the normality assumption is that the confidence intervals and tests performed no longer apply. However, they are not too badly affected and can be used as reasonable approximations, when the disturbance's distribution is not very radically different from normal [65, pp. 2^7-8]. , Validity of the normality assumption in the statistical model was evaluated through a direct examination of the residuals. All plots examined were found to have a pattern resembling very closely that of a normal distribution.

PAGE 192

174 Zero mean. --The zero mean assumption of the regression disturbance is based on the specification that the population regression line is E(Y.) = a + EBX.. If the mean of the disturbance values is, for example, y. , Instead of zero, then E(Y.) = a + EBX. + y.. When y. is a constant, E(Y.) = a"+ ZgX. , and the least squares formula gives an estimation of a-'-instead of a, though the least squares estimation of g's are unaffected. There exists no possibility in this case for est imat ing a and y separately and for obtaining unbiased or at least consistant estimates. When y. varies from observation to observation, I a becomes (a+ y.); thus, the dependent variable changes for both changes in the X.'s and for other reasons [65, pp. 248-9}. iThe above situation may be the result of specification error due to the exclusion of some relevant explanatory variables from the equation. An examination of the behavior of the regression residuals can be used to test for this specification error [65, p. 405] • In this case, the scrutiny of residuals in all the equations provides no reason to believe that the zero mean assumption of the model has been violated. Homoskedastici ty .--The characteristic of the regression disturbance known as homoskedast i ci ty implies a constant variance of the disturbance for all observations. When this does not hold, then E(e^) = a.^ I I which implies that the variance of the disturbance may vary from observation to observation. The least squares estimators, though still unbiased.

PAGE 193

175 cease to be BLUE, and, therefore, do not have the smallest variance in a class of unbiased estimators and are not efficient. They are still consistent but have lost the property of being asymptotically efficient. When heteroskedastici ty is present, confidence intervals and tests of hypotheses are meaningless [65, pp. 249-56; '59]Although the composition of the sample is such that variation among the variances of the disturbance is very unlikely, a test was conducted to corroborate that assertion. Total family income and total farm size are the only two variables with a possibility of violating the homoskedast ici ty assumption. When the disturbance was plotted against these two variables for each of the estimated equations, there appeared no reason to believe that this assumption would not hold in every equation. Sufficient observat ions .--Thi s assumption requires that the number of observations exceed the number of coefficients to be estimated, thus fulfilling the provision for a sufficient number of "degrees of freedom" in estimation. In all equations this assumption is satisfied; the number of observations always exceed the number of parameters. No mul t icol 1 inear i ty --No exact linear relationship should exist between any of the explanatory variables. When this assumption does not hold, perfect mul ti col 1 i near i ty is present.; However, mul t icol 1 inear i ty is a question of degree and, therefore, we do not test for multicollinearity but measure its degree in any particular sample. Perfect mul t icol 1 inear i ty causes the (X X) matrix in the leastI -It squares estimator 3= (X X) X Y to be singular. In the case of high but not perfect mul t icol 1 inear i ty , it becomes very difficult to disentangle the separate effects on the dependent variable of the independent

PAGE 194

176 variables. The result is the presence of large standard errors of the regression coefficients and the consequent widening of the acceptance region for the hypothesis that a given coefficient is zero. in turn, the possibility of making mistakes in accepting or rejecting hypotheses is very plausible. The no-mul t icol 1 inear i ty assumption was tested by closely examining the matrices of simple correlation coefficients of the independent variables (Table A-8 to Table A-26) . Only in 10 cases, out of a possible 399, do the variable combinations show a simple correlation coefficient larger than .50, but, in half the cases, these values are very close to •50. Those occur with total income and farm size (.51) in the corn equation for R (Table A-l4) and for R, (Table A-15). A value of .53 is observed between distance and farm size in the R^ wheat equation (Table A-26), total income and farm. size-, in the R^ corn-bean equation (Table A-10), and between distance and price in the R^ corn-bean-sorghum equation (Table A-12). Price and farm, size in the wheat equation of R. show a value of .59 (Table A-26). Larger values appear In a few instances. Price and distance present a value of .69 in the R^ wheat equation (Table A-26). Total income and price show a .62 in the R, sorghum equation (Table A-21), total income and farm size., of .81 in the R^ corn-sorghum equation (Table A-ll), and .8^ in the R, corn-beans-sorghum equation (Table A-12). Considering the small number of cases where variable combinations present a simple correlation coefficient larger than .50, and the specific circumstances when they occur, it is safe to infer that multicollinearity is not distorting the least-squares-estimates in any of the equations.

PAGE 195

177 Regression Results Results obtained from estimating tine equations are presented in Table A-27. Numerical values computed for depicting the income, total farm size, and price-quantity relat ionsiiips are also shown (Table A-28 to Table A-37) •

PAGE 196

178 Table A-8.--R corn-beans: simple correlation coefficients matrix of the independent variables W. P.

PAGE 197

179 Table A-10.--R, corn-beans: simple correlation coefficients matrix of tne independent variables E. A. W. 1 .00 0.33

PAGE 198

180 Table A-12.--R^ corn-beans-sorghum: simple corrleation coefficients matrix of the independent variables A. I . W. 1.00 0.22

PAGE 199

181 Table A-l'+.-'R. corn: simple correlation coefficients matrix of the independent variables

PAGE 200

182 Table A-16. — R corn: simple correlation coef f iciencts matrix of the independent variables

PAGE 201

183 Table A-18.--R beans: simple correlation coefficients matrix of the independent variables P. A. I . W. 1.00 0.^^

PAGE 202

I8ii Table A-20.--R/. beans: simple correlation coefficients matrix of the independent variables A. D. I W. I 1.00 -0.09 1.00 0.05 -0.17 1 .00 0.01 -0.01 0.00 1 .00 -0.09 -0.06 -0.30 -0.06 1 .00 -0.09 -0.11 -0.04 -0.02 -0.05 1.00 0.20 -0.05 0.31 -0.03 -0.23 -0.03 1 .00 Table A-21.--R, sorghum: simple correlation coefficients matrix of the independent variables P. A. D. W. Y. 1.00 0.01

PAGE 203

185 Table A-22.--R, rice: simple correlation coefficients matrix of the independent variables P. A. D. I . W. 1.00 O.H

PAGE 204

186 Table A-2^.--R^ rice: simple correlation coefficients matrix of the independent variables P. E. A. D. I. W. Y. I I I I I i I 1 .00 0.10

PAGE 205

187 Table A-26.--R, wheat: simple correlation coefficients matrix of the independent variables D. W. Y. 1 .00 0.05

PAGE 206

188 O o CO — LA CM I — rA o rA CO CA -3O o csj ro Itro csl — LA -Q -— rA-3— og v£) OO — LA tsj r^ CO <^ LA CO CTl O-v -3•— LA -3O vT) LA vD osir-^ cNicrycocnco— or^ rA LA r^ o-^ LA . — -3-^ O LA CAvD — r^ Of^ CVILA — ^r^-3ocM . — — . :r cocNi LArA O^CO -cr-:T cor^ r^co c-3vocTv v£)r^ r-~-r^ I I o i-^ csl — I -3-3-CO rsj rA r— LA -T CM -3r^ ^ -3C3 O — O O O O O LA SO O — I LA CO I OOsO cnco CGI — co^r -q-r-cM-3cMr^vocNi r^O'*\ • — • — LACO COLA CMLA OO O — — O OO OO OO OO OO c-v CM CA r^ CM O O C~\ LA C~\ -3rA — I CA ^^ CM CM O — O O O O O ^-N ^ — "O . — — O C7^ • — CO LA L.A cr-i cr> CM o CX3 CM LA CA CP. CA CM LA O -TO CO O CO -3CA VO LA LA CNI CA SO LA — CO I I CM CO — rLA i-~. r-~.so PA — O CA O O O o o o o o ^ UA o — o o o o o

PAGE 207

189 on O -3J-3-3-3XI -— -D ^-> -O — r-~ o-v — cr> cN CO CNj r^ r^ LA en — r^ (r> • :r — r~^ CO CO vo o -doo CTv COO vDO v£> — COfM ^-vO LALTvCOO Lr\\D cN-^ coro cna~\ o^, ^o c^r — . — — r^^o — CM est r^ ro — o Lr\ CNJ — — njD r^ r-^ u-v o -:r ro r^ U\ O O^ I 1 I I — r-^ O do I r^vo r^o cnr^ csjco cNir'^ voco lao vOcM ocvj vD-c ro— i^^cN r^^r Lnco OO co^^ \£) • — 0(N • — CNi o\0 -iru'"^ o a o a oo o o o o — o ^-o oo oo oo oo oo oo oo oo oo oo oo oo oo CO O r^ CNl O o o o o o o Ln -3CM r^ ^ o — o o o o o o o o o o o o o o o o o o o o o -3— o o o o o o o o O CM Csl O o o c o o o r^ C o o o o o o oo oo oo oo o o oo oo I I I o -3CO CO so -3CM o o o o o o o o o o o o o o o o o o o o o o o o I O CO CM r^ LA so o o o o I 3o o o o o o oo oo o o oo oo oo t -a — ^^ ,-^ -o ^^ roo o-^O OO sOO COrA roso soro OCO -3--3' sOCsJ CMCM COCTl O^sO r^i sO • — CM CMf^ OO OO OO — O OO OO oo oo O CTi r^ — SO o^ r-CO O so O so CM C^ r*^ ^O — O O O o I — I CNI CO — CM o o o o o o o o 1 ^-' so CO sD 0'> O f-^ O O O O in

PAGE 208

90 1

PAGE 209

191 00 1 en

PAGE 210

192 I CO I vO 3 •a (U Q. TO !_ O) -Q TO to I >JD CO I o VO m t_) LA 03 I CSvD-3-v£)CO0O U-\-3-vD LAO CM Cy — LALAvOrOCOCNILAr^-Cn — CM CTirALAvo t^-r^oocooooo cr\cn ' CNJCNiCNlCNICSlCSlCSCMCNlCvJCSI r^cNicMcMcs-cr-:rcrv-^MDr — 3_ r-^CNjocNi-3--3-. — cncMorooo cy o^oococTiMD — unr^ocNjLn-gMD OCNir^-3-Lr\LALAv£>vOvOvD • — CSICSCMCMCSJcslCMCMCNjrslCM CO Lncr\oo i — r-~LAi-^r»^r^i — i — — oor-~r~^f^r^ocNi-:3-Lav£)r~-. o* -3-cr\^ — cNiooraoiAOOOCOCX)OOCr»rsJO _ OOlAOCOv£)r^v£)CNJ[^— LAOO O" ODroCTV' — rO-3-UAvDv.Or^r^r^ LAr-^r^oooocooocxDcocooo o^ cnLAvDvDcS' — r^o-a-. — cocni cy r^-=rocr> — o~>-crcr\rv)LAr^cr\ OOOOCNlOOLALAvDvOr-^r-^l — I — O. — 00 — -— . ^^__^ ror^r^o— cor — d-o — cm-3cy tA-3--3-r--roocaoa— r^CNIvD r^OOvD O roLAvD r-^OOOO CT^CTv J csl' — • — oocp\r-~.oor~-t>-»cr\ro O" LAv^-a-OOOCM^TLALAvOvOr^ r-^o^oo — — — — — — — — i — — CSJCMCNCVJCNCSJCMCNICNICNI a. o->^0 a~\CM LAOO — -3rv.o rovO OOO — • — — CNCNCMo^rAf*-! oooooooooooo OJ

PAGE 211

193 0) CD 0) JC CL
PAGE 212

]Sk 0) jr D. fO 1_ cn c o o 1_ o in Q. j: 1/1 c o
PAGE 213

195 Table A-33 • ~~Pr ice-quant i ty relationships for corn graphed in Figure 13

PAGE 214

196 Table A-3'+. — Income-quantity relationships for beans graphed in Figure \h

PAGE 215

197 Table A-35--I ncome-quant i ty relationships for ricegraphed in Figure 15

PAGE 216

198 Table A-36.--Farm size-quantity relationships for rice graphed in Figure 1 6 o

PAGE 217

199 Table A-37.~~Farm size-quantity relationships for wheat graphed in Figure 1 7

PAGE 218

REFERENCES Abbott, J.C. "Marketing Issues in Agricultural Development Planning." Markets and Mar ket ing in Developing Economies , eds., Moyer R. , and S.C. Hollander. Homewood , Illinois: Richard D. Irwin, I968. . "The Development of Marketing Institutions.," Agricultural Development and Economic Growth , eds., H. Southworth and B.F. Johnston. N.Y.: Cornell University Press, 1967. "The Role of Marketing in the Development of Backward Agricultural Economies," Marketing and Economic Development-Readings in Agribusiness Research , ed . , Clarence J. Miller. Lincoln, Nebraska: University of Nebraska Press, 1967. A, Andrew, Chris 0. "Marketing Needs of Small Farmers under Multiple Cropping Systems." Staff Paper 3, Food and Resource Economics Department, University of Florida, April, 1975. 5. Andrew, Chris 0., et_ aj_. Problemas de Mercadeo y Produccion del Campes ino . Boletin Teen i co No. 10, Instituto Colombiano Agropecuar io, Ministerio de Agricultura, March, 1971. 6. Bardhan, Kalpana. "Price and Output Response of Marketed Surplus of Foodgrains: A Cross-Sectional Study of Some North Indian Villages." American Journal of Agricultural Economics 52 (1970): 51-61. 7. Bateman, Merrill J. "Supply Relations for Perennial Crops in the Less Developed Areas." Subsistence Agriculture and Economic Development , ed . , C.R. Wharton, Jr. Chicago, Illinois: Aldine Publishing Co., 19698. Bauer, P.T., and B.S. Yamey. "A Case Study of Response to Price in an Underdeveloped Country." The Economic Journal 69 (1959): 800-805. 9. Behrman, Jere R. "Price Elasticity of the Marketed Surplus of a Subsistence Crop." Journal of Farm Economics ^8 (I966): 875-893. 200

PAGE 219

201 10. . "Supply Response and the Modernization of Peasant Agriculture: A Study of Four Major Annual Crops in Thailand." Subsistence Agriculture and Economic Development , ed. , C.R. Wharton, Jr. Chicago, Illinois: Aldine Publishing Co., 19691 1 . . Supply Response in Underdeveloped Agriculture . Amsterdam: North-Holland Publishing Co., I968, 12. Biggs, Huntley H. , and R.L. Tinnermeier, eds. Smal 1 Farm Agricultural Development Problems . Colorado: Colorado State University, I97A. 13. Bonnen, J.T., O.K. Eicher, and A. Allan Schmid. "Marketing in Economic Development." Agricultural Market Analysis-Development, Performance, Process , ed. , V.L. Soreson, pp. 35-^9, Michigan: Michigan State University Press, 1964. 14. Chaturvedi, J.N. The Theory of Marketing in Underdeveloped Countries , Chapter 10. Delhi, India: Kitab Mahl Publishers, 1959. 15. Chinn, Dennis L. "The Marketed Surplus of a Subsistence Crop: Paddy Rice in Taiwan." American Journal of Agricultural Economics 58 (1976): 583-58716. Collins, N.R., and R.H. Holton. "Programming Changes in Marketing in Planned Economic Development." Agriculture in Economic Development , eds., C. Eicher and L. Witt, pp. 359-369N.Y.: McGraw-Hill Book Company, 1964. 17Corisco, Amalia. Estudio de la Comunidad de Santo Domingo Xenacoj , Departmento de Sacatepd'quez . Guatemala: Socioeconomia Rural, fCTA. In Process. 18. Currie, Lauchlin. "Marketing Organization for Underdeveloped Countries." Markets and Marketing in Developing Economies , eds., Moyer, Reed and S.C. Hollander. Homewood, Illinois: Richard D. Irwin, I968. 19. Daines, Samuel R. Guatemala Farm Policy Anal ys I s--The Impact of Small-Farm Credit on Income, Employment, and Food Production . Washington, D.C.: Agency for International Development, April 1975. 20. Dean, Edwin R. "Economic Analysis and African Response to Price." Journal of Farm Economics 47 (1965): 402-409-

PAGE 220

202 2 1 . . The Supply Responses of African Farmers: Theory and Measurement in Malawi . Amsterdam: North Holland Publ ishing Co. , 1966. 22. Diario La Tarde. Afio Vi, No. I6l4, Guatemala, Martes 20 de Enero de 1976. 23. Dixit, A.K. "Marketable Surplus and Dual Development." Journal of Economic TKeory 1 [1969): 203-219. 2k. Dombrcwski, John, et al. Area Handbook for Guatemala . DA Pam 550-78. Washington, D.C.: The American University, March 1970. 25. Dorner, Peter., ed. "Policy Implications." Land Reform in Latin AmericaI ssues and Cases . Madison: Land Economics Monograph No. 3, University of Wisconsin, 1971. 26. Dorner, Peter and Don Kanel. "The EconomTc Case for Land Reform: Employment, Income Distribution, and Productivity." Land Reform in Lat in-Amer ica-I ssues and Cases , ed., Peter Dorner, pp. 41-56. Madison: Land Economics Monograph No. 3> University of Wisconsin, 1971. 27. Dovring, Folke. "The Share of Agriculture in a Growing Population." Agriculture in Economic Development , eds., C. Eicher and L. Witt, pp. 78-98. N.Y.: McGraw-Hill Book Co. , 1964. 28. Drucker, Peter F. "Marketing and Economic Development." The Environment of Marketing Behavior--Select ions from the Literature , eds., R.J. Holloway and R.S. Hancock, pp. 333" 338. N.Y.: John Wiley & Sons, 1964. 29. Dubey, Vinod. "The Marketed Agricultural Surplus and Economic Growth in Underdeveloped Countries." Economic Journal 73 (1963): 689-702. 30. Durbin, J. and G.S. Watson. "Testing for Serial Correlation in Least-Squares Regression, I." Biometrika 37 (1949): 409-428. 31. Falcon, Walter P. "Factor Response to Price in a Subsistence Economy: The Case of V/est Pakistan." American Economic Review 54 (1964): 580-591. 32. . "The Green Revolution: Generation of Problems." American Journal of Agricultural Economics 52 (1970): 698710.

PAGE 221

203 33. Fisher, Franklin M. "A Theoretical Analysis of the Impact of Food Surplus Disposal on Agricultural Production in Recipient Countries." Journal of Farm Economics ^5 (1963): 863-875. 3^. Fletcher, L.B. "Commodity Markets and Market ing!'.' Economic Development of Agr icul ture--The Modernization of Farming , ed. , Ames, Iowa: Iowa State University Press, 1 965. 35. Fletcher, L.B., et al . Guatemala's Economic Development--The Role of Agr icul ture . Ames, Iowa: The Iowa State University Press, 1970. 36. Gaitskell, Arthur. "Importance of Agriculture in Economic Development." Economic Development of Tropical Agriculture , ed., W.W. McPherson. Gainesville, Florida: University of Florida Press, 1968. 37. George, P.S., and G.A. King. Consumer Demand for Food Commodities in the United States with Projections for I98O . California: University of California, Division of Agricultural Sciences, Giannini Foundation Monograph 26, March 1971. 38. Ghoshal, Animesh. "The Price Responsiveness of Primary Producers: A Relative Supply Approach.'-' American Journal of Agricultural Economics 57 (1975): II6-II8. 39. Haessel, Walter. "The Price and Income Elasticities of Home Consumption and Marketed Surplus of Foodgralns." American Journal of Agricultural Economics 57 (1975): 111-115kO. Harrison, Kelly. Agricultural Market Coordination in the Economic Development of Puerto Rico . Ph.D. Dissertation, Michigan State University, I966. ^1. , "Approaches to Integration of Rural Urban Food Marketing Systems in Latin America." Paper presented to the Agricultural Development Council Workshop on Agricultural Marketing in Developing Countries, Lexington, Kentucky, October 7-9, 1971. kl . . Development, Unemployment, and Marketing in Latin America . Occasional Paper No. 2, Latin American Studies Center, Michigan: Michigan State University, April 1972. A3. Harrison, Kelly and Kenneth Shivedel. "Marketing Problems Associated with Small Farm Agriculture." Report on an ADC/RTN Seminar held at Michigan State University, June 7-8, 197'*. N.Y.: The Agricultural Development Council, Inc., November 197^.

PAGE 222

20^ kh. Harrison, Kelly et_ aj_. Improving Food Marketing Systems in Develop ing Countrfes: Experiences from Latin America . Research Report No. 6, Latin American Studies Center, East Lansing, Mictiigan: Michigan State University, November 197^kS. Heady, Earl and Leo Mayer. "Balancing the Flow of Resources between Production and Marketing." The Marketing Challenge-Distributing Increased Production in Developing Nations , ed. Martin Kriesberg. Washington, D.C.: U.S. Department of Agriculture, Foreign Economic Report 7, December 1970. 46. Heady, Earl 0. "Processes and Priorities in Agricultural Development." Economic Development of Tropical Agriculture , ed. W.W. McPherson. teinesville, Florida: University of Florida Press, I968. 47. Hill, George W. , and M. Col las. The Minifundia Economy and Society of the Guatemalan Highland Indian . Wisconsin: University of Wisconsin, Land Tenure Center, Report No. 30, July I968. k8. HIrschman, Albert 0. The Strategy of Economic Development . New Haven, Conn.: Yale University Press, I966. 49. Holloway, R.J. and R.S. Hancock., eds. The Environment of Marketing Behavior--Select ions from the Literature . N.Y.: John Wiley S Sons, Inc. , 1964. 50. Hussain, Syed M. "A Note on Farmer Response to Price in East Pakistan." Pakistan Development Review k (1964): 93-106. 51. IBRD. The Economic Development of Guatemala . Washington, D.C.: Jnternational Bank for Reconstruction and Development, 1951. 52. ICTA. "Evaluacidh del Trabajo del I CTA en la Cooperative Santa LucTa. R.L., Departamento de Solold" y con el Programa de Vecinos Mundiales, Depto. de Ch imal tenango." Guatemala: ICTA, SocioeconomTa Rural, August 1975Mimeo. 53• "Programa de Socioeconomra Rural." Guatemala: ICTA. Mimeo. 54. INDECA. Algunos Aspectos de ProduccTon y Comercial izac Tdn de MaTz y Frijol en Varias Regiones del Pai'^s . Guatemala: INDECA, June 1971 . 5 5 . • Comercio I nternac ional y Noticias de Mercadeo Interno de Productos AgrTcolas . Guatemala: INDECA, Division Tecnica, Quarterly Issues.

PAGE 223

205 56. . Noticias de Mercadeo de Productos Agrrcolas . Guatemala; INDECA, Depto de Invest tgac ion , Capacitacion y Extensfon de Mercadeo, Monthly Issues. 57. Johnson, Glenn L. "Factor Markets and Economic Development." Economic Development of Tropical Agriculture , ed. W.W. McPherson. Gainesville, Florida: University of Florida Press, 1968. 58. Johnston Bruce F. , and John V/. Mel lor. "The Role of Agriculture in Economic Development." Leading Issues in Developing Economics , ed. Gerald M. Meier, pp. 291-297. N.Y.: Oxford University Press, 195'*. 59. Johnston, J. Econometric Methods . N.Y.: McGraw-Hill Book > Company, Inc. , 1972. -^ 60. Kahlon, A.S., and H.N. Dwlvedi. "Interrelationships Between 7 Production and Marketable Surplus." Asian Economic Revi ew 5 \ (1963): kl\-m. ' 61. Khan, A.R., and .A.H.M. Nuruddin Chowdhury. "Marketable Surplus Function: A Study of the Behavior of West Pakistan Farmers." Pakistan Development Review 2 (I962): 354-376. 62. Khan, M.H. "Real Effects of Foreign Surplus Disposal in Underdeveloped Economies: Comment." Quarterly Journal of Economics 78 (1964): 348-349. 63. Khatkhate, Deena R. "Some Notes on the Real Effects of Foreign Surplus Disposal in Underdeveloped Economies." Quarterly Journal of Economics 76 (1962): I86-I96. 64. King, Richard A. "Product Markets and Economic Development." Economic Development of Tropical Agriculture , ed. W.W. McPherson. Gainesville, Florida: University of Florida Press, 1968. 65. Kmenta, Jan. Elements of Econometrics . N.Y.: The Macmillan Company, 1 971 • 66. Kriesberg, Martin., ed. The Marketing Chal lenge--Di str ibut ing Increased Production in Developing Nations . Washington, D.C.: U.S. Department of Agriculture, Foreign Economic Development Report 7, December 1970. 67. Kriesberg, Martin and Howard Steele. Improving Marketing Systems in Developing Count r ies--An Approach to Identifying Problems and Strengthening Technical Assistance . V/ashington, D.C.: U.S. Department of Agriculture, Foreign Agricultural Economic Report No. 93, February 1972.

PAGE 224

206 68. Krishna, Raj. "Agricultural Price Policy and Economic Development," AgrTcultural Development and Economic Growth , eds., H. Southworth and B.F. Johnston, pp. ^97-5^7^N.Y.: Cornell University Press, 196769. . "A Note on the Elasticity of the Marketable Surplus of a Subsistence Crop." Indian Journal of Agricultural Economics 17 C1962): 79-84. 70. . "Farm Supply Response in India-Pakistan: A Case Study of the Punjab Region." Economic Journal 73 (1963): kn-kZl. 71. . "The Marketable Surplus Function for a Subsistence Crop." Economic Weekly Annua] Volume (1965): 309-320. 72. Krishran, T.N. "The Marketed Surplus of Food Grains: Is It Inversely Related to Price?" Economic Weekly 17 (1965): 325-328. 73. Larzelere, Henry. "Cooperatives in Agricultural Marketing." Agricultural Market Analysis-Development, Performance , Process , ed., V.L. Soreson, pp. 205-216. Michigan: Michigan State University Press, 1964. 74. Lewis, W. Arthur. "Economic Development With Unlimited Supplies of Labour." The Manchester School , May 195^. 75. MacDonald, Charles et_ aj_. Agriculture-Guatemala-Statistical V/orking Document #\% — A Close Look at Some Statistics from the 1974 Guatemala Small Farm Survey . Washington, D.C.: Sector Analysis Division, Bureau for Latin America, Agency for International Development, January 197576. Manghas ,^ M. , Aida E. Recto, and V.W. Ruttan. "Price and Market Relationships for Rice and Corn In the Philippines." Journal of Farm Economics 48 (I966): 685-703. 77. Mathur, P.N., and H. Ezekiel. "The Marketable Surplus of Food and Price Fluctuations in a Developing Economy." Kyklos 14 (I96I): 396-406. 78. Medani, A.I. "Elasticity of the Marketable Surplus of a Subsistence Crop at Various Stages of Development." Economic Development and Cultural Change 23 (1975): 421-429. 79. Mehren, George L. "Market Organization and Economic Development." Journal of Farm Economics 4l (1959): 1307-1315-

PAGE 225

207 80. Meier, Gerald M. , ed . Leading Issues in Development Economics . N.Y.: Oxford University Press, 196^. 81. Mellor, John W. "The Agricultural Marketing System and Price Stabilization Policies." Ithaca, N.Y.: Cornell University Press, Staff Paper No. 26, December 1970. 82. Miracle, Marvin P. "Subsistence Agriculture: Analytical Problems and Alternative Concepts." American Journal of Agricultural Economics 50 (1968): 292-310. 83. Moyer, Reed. "Marketing in Economic Development." East Lansing, Michigan: Michigan State University, Institute for International Business Studies, Occasional Paper No. 1, 1965Sh. Moyer, R. , and S.C. Hollander., eds. Markets and Marketing in Developing Economies . Homewood, Illinois: Richard D. Irwin, Inc., 1968. 85. Mubyarto. "The Elasticity of the Marketable Surplus of Rice in Indonesia: A Study in Java-Madura." Ph.D. Dissertation, Iowa State University, 1965. 86. Mueller, Willard F. "Some Market Structure Considerations in Economic Development." Journal of Farm Economics ^1 (1959): ^^-425. 87. Narain, Dharm. Distribution of the Marketed Surplus of Agricultural Produce by Size-Level ot Holding in India l^t? u~t?l . Del hi , Bombay: Asia Publishing House, 1 961 . 88. Nason, Robert W. , ed. The Role of Food Market Tng in the Economic Development of Puerto Ri co--Seminar Summary . East Lansing, Michigan: Michigan State University, Latin American Studies Center, I966. 89. Nicholls, William H. "The Place of Agriculture in Economic Development." Agriculture in Economic Development , eds., C. Eicher and L. Witt. N.Y.: McGraw-Hill Book Co., 196^*. 90. Oldenstadt, D. , and David Call. "Group Action in Agricultural Marketing." Agricultural Market Anal ys is--Development , Performance, Process , ed. V.L. Soreson. Michigan: Michigan State University, 196't. 91. Olson, R.O. "Discussion: Impact and Implications of Foreign Surplus Disposal in Underdeveloped Economies." Journal of Farm Economics 42 (I96O): 10'42-1045.

PAGE 226

208 92. O'Quinn, Floyd. General Working Document ;g50--Descr ipt ive Tables of Guatemala Small Farm Survey . Washington, D.C.: Sector Analysis Division, Bureau for Latin America, Agency for international Development, May 1975. 93. Papanek, Gustav F. "Development Problems Relevant to Agriculture Tax Policy." Papers and Proceedings of the Conference on Agricultural Taxation and Economic Development , pp. 193-196. Cambridge, Mass.: Harvard Law School, 195^94. Patrick, George F. , et_ aj_. , eds. Small-Farm Agriculture: Studies in Developing Nations . Indiana: Purdue University, Agricultural Experiment Station, Department of Agricultural Economics, September 197595. Pearson, Harry W. "The Economy H^as N-o Surplus: Critique of a Theory of Development." Trade and Markets in the Early Empires , ed . K. Polanyi, CM. Arensberg, and H.W. Pearson, p. 339. Glencoe, Illinois: Free Press, 1957. 96. Perrin, Richard and Don Winkelmann. "Impediments to Technical Progress on Small versus Large Farms." American Journal of Agricultural Economics 58 (1976): 888-89^r 97. Prebisch, Raul. "Commercial Policy in the Underdeveloped Countries, Leading Issues in Development Economics , ed. Gerald M. Meier, pp. 286-289. N.Y. : Oxford University Press, 196'*. 98. Proenza, Francisco J. "Produccrdn de MaTz en Guatemala — Diferencias Tecnolcfgicas, Adopci'on de Insumos Modernos y el Programa de Asistencia al Pequeno Agricultor." Washington, D.C.: U. S.D. A. -E.R.S., December 1975, In Process. 99. Recto, Aida E. "Price and Market Relationships for Corn in the Philippines." Unpublished Master's thesis. University of the Phil ippines, I965. 100. Reynolds, A.E. "Effects of Technology on Marketing." The Environment of Marketing Behavior--Select ions from the Literature , eds., R.J. Holloway and R.S. Hancock, pp. 15'*-157. N.Y. : John Wiley & Sons, 1964. 101. Ricardo, Jos^ M. General Working Document /i'51 --Eval uat ion of Technical Assistance Impacts on Small Farmers' Performance of Guatemala Small Farm Survey . Washington, D.C.: Sector Analysis Division, Bureau for Latin America, Agency for International Development, June, 1975-

PAGE 227

209 102. Riley, Harold. "Evaluation of Marketing Systems in Latin America. A paper presented to the Markets and Trade and Economic Development Workshop, North Carolina State University, Raleigh, North Carolina, February 20, 1968. 103. . "Improving Internal Marketing Systems as Part of National Development Systems." Michigan: Michigan State University, Latin American Studies Center, Occasional Paper No. 3, May 1972. 104. • • Market Coordination in the Development of the Cauca Valley Region — Colombia . East Lansing, Michigan: Michigan State University, Latin American Studies Center, Research Report No. 5, March 1970. 105. Riley, Ha ro 1 d e^ a_l_. Food Marketing in the Economic Development of Puerto Rico. East Lansing, Michigan: Michigan State University, Latin American Studies Center, Research Report No. ^, July 1970. 106. Robertson, Thryele £1 a^Agr icul ture — Guatemala — Methodolog ical Working Document 751 • Washington, D.C.: Sector Analysis Division, Bureau for Latin America, Agency for International Development, February 1975107. Ruano, Sergio. "El Altiplano: i Una Zona Maicera en el Futuro?." Guatemala: ICTA, Socioeconomfa Rural. Typed. 108. Schultz, TKeodore W. Transforming Traditional Agriculture . New Haven, Conn.: Yale University Press, 1969109. • "Value of U.S. Farm Surpluses to Underdeveloped Countries." Journal of Farm Economics A2 (1960): 1019-1030. 110. Scott, CD. Some Problems of Marketing Among Small Peasant Proprietors in Chile . Madison, Wisconsin: University of V/isconsin, Land Tenure Center, June 197^. 111. Sen, S.R. "Impact and Implications of Foreign Surplus Disposal on Underdeveloped Economies--The Indian Perspective." Journal of Farm Economics ^2 (I960): 1031-1042. 112. Shaw, Arch W. "Some Problems in Market Distribution." The Environment of Marketing Behavior — Selections from the Literature , eds., R.J. Holloway and R.S. Hancock, pp. 5-9N.Y.: John Wiley & Sons, 1964. 113. Stern, R.M. "The Price Responsiveness of Egyptian Cotton Producers." Kyklos 12 0959): 375-384.

PAGE 228

210 ]]h. Stern, R.M. "The Price Responsiveness of Primary Producers," Review of Economics and Statistics hk (1962): 202-207. 115. The Agricultural Development Council. "Marketing Institutions and Services for Developing Agriculture." Report on an ADC/RTN Seminar held in Washington, D.C., September 10-12, 1974. N.Y.: The Agricultural Development Council, Inc., July 1975. 116. Toquero, Zenaida, Bart Duff, Teresa Anden, and Yujiro Hayami. "Marketable Surplus Functions for a Subsistence Crop: Ri;ce in the Philippines." American Journal of Agricultural Economics 57 (1975): 705-709117. U.S. Department of Agriculture. Agricultural Trade of the Western Hemisphere — A StatisFica! Review, 1963-73 Washington, D.C,: U.S. Department of Agriculture, E.R.S. Statistical Bulletin No. 5^6, July 1975. 118. Waugh, Robert K. The Institute of Agricultural Science and Technology of Guatemala (Instituto de Ciencia y TecnoTogfa AgrTcolas) ICTA — Four Years of History^ Guatemala : ICTA, September 1975. 119. Wharton Jr,, Clifton R. Subsistence Agriculture and Economic Development . Chicago, Illinois: Aldine Publishing Co., 1969. 120. Wiens, Thomas B. "Peasant Risk Aversion and Allocative Behavior; A Quadratic Programming Experiment." American Journal of Agricultural Economics 58 (1976): 629-635121. Witt, L., and Carl Eicher. The Effects of United States Agricultural Surplus Disposal Programs on Recipient Countries . East Lansing, Michigan: Michigan State University, Department of Agricultural Economics Research Bulletin No. 2, 196^. 122. Zarembka, P. "Marketable Surplus and Growth in the Dual Economy.' Journal of Economic Theory 2 (1970): 107-121.

PAGE 229

BIOGRAPHICAL SKETCH Jose Alvarez was born in Oriente, Cuba, on December 10, 19^40. He attended Law School in Oriente University and Havana University. In February, 1969, he came to the United States. He received his Bachelor of Arts degree with a major in economics, with honors, from the University of Florida, in December, 1971, and his Master of Science in Agriculture in August, 197^He is now a candidate for the degree of Doctor of Philosophy. He is a member of the American Agricultural Economics Association, the American Economic Association, the Southern Agricultural Economics Association, Omicron Delta Epsilon, and the Society for International Development. He is married to the former Mercy Fernandez and has two children, Mercita and Ricardo Jos^. 211

PAGE 230

I certify that I have read this study and that in my opinion conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. I C.O. Andrew, Chairman Associate Professor of Food and Resource Economics I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Leo Polopolus Professor of Food and Resource Economi cs I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. KrwvoUO.uXwi R.W. Ward Associate Professor of Food and Resource Economics I certify that I have read this study and that in my opinion conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. t 0.(0, ~)] IS^A.i^-^--'k .W. McPhcrson Graduate Research Professor of Food and Resource Economics

PAGE 231

I certify that I have read this study-arid thnt in my oiiinion conforms to acceptable standards of scholar/y presentation and is fully adequate, in scope and quality, as a/ d'\ssj^ri-^l/^n for the degree of Doctor of Philosophy. I t L J. Carvajal Assistn'rrt P/ofcssor for the. Center for L^jtin American Studies^ This dissertation was submitted to the Graduate Faculty of the College of Agriculture and to the Graduate Council, and was accepted as partial fulfillment of the requirements for the degree of Doctor of Phi losophy. June 1977 /. t 'I Dea/f,' College of Agriculture Dean, Graduate School

PAGE 232

f\ ^


TRADITIONAL
IN
THE CASE
AND COMMERCIAL FARM SUPPLY RESPONSE
AGRICULTURAL DEVELOPMENT:
FOR BASIC GRAINS IN GUATEMALA
By
Jose Alvarez
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1977

A los pequeños agricultores del Altiplano Central que conoci" durante
mi breve estadiá en Guatemala:
-A los que perecieron a consecuencia del terremoto del b de
Febrero de 1976, como sencillo tributo a su laboriosidad y
hospital idad;
-A los sobrevivientes de la catástrofe, con la esperar.za de
que el futuro les depare la prosperidad que nunca han tenido
y que tanto merecen.
A la nostalgia que produce la imposibilidad de hacer esta
investigación sobre los guajiros de mi Cuba,pero compensado
por haberla hecho por los de ese pedazo de América por el que
José" Marti" sintió’ especial devoción.

To the small farmers of the Central Highlands I met during my short
stay in Guatemala:
-To those who died because of the earthquake on February 4th,
1976, as a humble tribute to their diligence and hospitality;
-To the survivors of that catastrophe, hoping that the future
will bring them the prosperity they have never had and so much
deserve.
To the nostalgic feeling produced by the impossibility of conducting
this research on the qua ji ros of my Cuba, but compensated for having
done it on those from that part of Latin America for which José Mart
felt special devotion.

ACKNOWLEDGMENTS
In most cases, every research product is the result of multiple
endeavors. This one Is no exception. Sinceitsvery beginning, many
persons and institutions have provided enormous contributions. With¬
out them this dissertation would never have been possible. The list
is long as deep is my indebtedness.
Special thanks go to every member of my Supervisory Committee:
To Chris 0. Andrew, my chairman, for his help, patience, and encourage¬
ment not only during every phase of this research but throughout all
these years of graduate work; to Ronald W. Ward for always being
available to share his knowledge of Econometrics and for his valuable
comments; to W.W. McPherson, who taught me the theoretical background
of Economic Development, for providing his experience in the area
through sound remarks; to Manuel J. Carvajal for his help in this
dissertation and his availability during all these years; to Leo
Polopolus, Department Chairman, for his support, his comments and the
financial assistance of the Department.
My appreciation to the Institute of Agricultural Science and
Technology (ICTA) of Guatemala, particularly to Mario Martfnez and
Astolfo Fumagalli, for the enthusiasm shown in approving the research

topic. Special thanks to my friends in SocioeconomTa-ICTA, starting
with the Coordinator, Peter E. Hildebrand. His vast experience with
the Guatemalan situation materialized in helpful comments and ideas
during several reviews of the manuscript. To Pete and Joyce, his
wife, thanks also for their hospitality and understanding.
I am grateful to the Rockefeller Foundation, especia 11 y to Joe
D. Black, for willingness to finance the original project. And to
International Programs-1 FAS, University of Florida, for making some
funds available at an early stage of.the research.
The Consejo Nacional de Planificación Económica de Guatemala
deserves credit for authorizing use of the Farm Policy Analysis data
utilized in this study. Russell Misheloff, Daniel A. Chaij, Robert
Bartram, and James Riordan, USAID-Washington, facilitated release of
the tapes and Carl D. Koone, USA ID-Guatemala, was a most valuable
intermediary.
My appreciation to Sheriar Irani and Mario Ariet for writing and
debugging so many computer programs. The facilities of the Northeast
Regional Data Center of the State University System of Florida were
used for making all computations.
Special thanks to Beth Davis and Ann Ritch for valuable assistance
in typing so many drafts and to Beth Davis again for typing the final
copy.
Finally, and above all, I want to thank my wife, Mercy, for her
love and encouragement in both good and difficult times. She and I
owe too much to Mario and Nini Ariet and want to thank them for being
always there.
v

TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS iv
LIST OF TABLES x
LIST OF FIGURES xiv
ABSTRACT xvi
CHAPTER
I INTRODUCTION 1
Setting of the Study 1
Physical Environment 1
Population 2
Government and Political Subdivisions. 3
The Economy 5
Agriculture 6
Markets and Marketing 7
Foreign Trade 8
Setting of the Problem . 10
Introduction 10
Problem Statement 15
Object i ves of the Study 25
Data Source and Data Considerations .... 25
Relevance of the Project. . . • 31
Organization of the Dissertation 32
II AN EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT . 33
Agriculture and Economic Development. ... 33
Agriculture in LDCs: A Changing
Spectrum of Priorities 3^
Agriculture versus Industry: A False
Issue 36
The Role of Agriculture in Economic
Development 37
Some Prescriptions for Agricultural
Development 39

CHAPTER
Page
Marketing and Economic Development h2
Marketing Defined ^2
The Role of Marketing in the Economy. . ^3
The Role of Marketing in Economic
Development ^
Marketing and the Theory of Demand in
LDCs 50
Marketing and the Theory of Supply in
LDCs 52
ill THEORETICAL AND METHODOLOGICAL FRAMEWORK FOR
INVESTIGATING TRADITIONAL AND COMMERCIAL FARM
SUPPLY RESPONSE 56
Basic Economic System of the Guatemalan 56
Small Farmer
Method of Estimation Sk
Hypotheses 6^
The Model 66
Adaptation of the Model 69
Production and Distribution Activities ... 70
Data Used and Implications 70
Summary 72
IV PRODUCTION AND DISTRIBUTION ACTIVITIES 73
The Input Market 73
Seed Utilization 73
Urea Application 78
Soil Additives 80
Other Chemicals 80
Other Fertilizers 80
Pesticides 8l
Labor 81
The Product Market 82
Total Production 82
Animal Feed and Seed 82
Family Consumption 87
Processing 87
Rent Payments 88
Sales "in Kind" 88
Donations 88
Total Losses 88
Cash Sales 89
Marketing Expenditures 89
Summary 90

CHAPTER
Page
V TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE. . 93
Associations 93
Regression Coefficients 106
Income-Quantity Relationships 1 08
Farm Size-Quantity Relationships .... 109
Price-Quantity Relationships 109
Corn 109
Regression Coefficients 110
Income-Quantity Relationships 1 1 b
Farm Size-Quantity Relationships .... 11^
Price-Quantity Relationships 115
Beans 116
Regression Coefficients 116
Income-Quantity Relationships 118
Farm Size-Quantity Relationships .... 1 13
Price-Quantity Relationships 119
Sorghum 119
Regression Coefficients 119
Income-Quantity Relationships 120
Farm Size-Quantity Relationships .... 120
Price-Quantity Relationships 120
Rice 121
Regression Coefficients 121
Income-Quantity Relationships 12^
Farm Size-Quantity Relationships .... 12^
Price-Quantity Relationships 12^
Wheat 126
Regression Coefficients 126
Income-Quantity Relationships 128
Farm Size-Quantity Relationships .... 129
Price-Quantity Relationships 129
Summary 129
VI SUMMARY, CONCLUSIONS, IMPLI CAT 10NS. AND RECOMMEN¬
DATIONS 131
Problem and Objectives 131
Research Findings 133
Production and Distribution Activities . 13^
Trad i t ional and CornmerciaT -Farm Suppl y
Response W.' .r r. . . . 135
Data Generza1izations and Implications. . . . 137
Errors and Omissions in Data Recording . 138
Upward or Downward Bias 139
VIII

CHAPTER
Page
Education of household head 140
Distance to the market 140
Total farm size 140
Total family income 141
Farmgate price 141
Quantity demanded on the farm. ... 142
Relative profitability ratio .... 142
Conclusions and Recommendations 143
VII REFLECTIONS ON THE THEORY OF DEVELOPMENT 147
Introduction 147
The Green Revolution: Generation Problems
and Small Farm Development 149
First Generation 149
Second Generation 152
Third Generation 153
Suggestions for Further Researcn 155
Epilog 156
GLOSSARY 158
APPENDIX 161
List of Crops 161
The Mathematical Model I6l
The Statistical Model: Its Assumptions and
Possible Violations 172
The Regression Model 172
Possible Violations of the Assumptions. . 173
Normal i ty 173
Zero mean 174
Homoskedasticity 174
Sufficient observations 175
No muíticol 1¡nearity 175
Regression Results 177
REFERENCES 200
BIOGRAPHICAL SKETCH 211
x

LIST OF TABLES
Table Page
1 Guatemala's imports and exports of cereals,
1963-72 9
2 Guatemala's agricultural imports and exports,
total imports and exports, and agricultural
percentage of total, 1963“72 11
3 Average wholesale prices for beans and corn, in
Guatemala City, 1972 20
A Average wholesale prices for beans and corn, in
Guatemala City, 1973 21
5 Average wholesale prices for beans and corn, in
Guatemala City, 197^ 22
6 Number of sampled farms by region and farm size. . 28
7 Number of sampled farms by region, sub-region,
and department 29
8 Total inputs used in basic grain' production by
regions of Guatemala ~/k
9 Relative importance of inputs used in basic grain
production by regions of Guatemala 76
10 Seed purchase and sale proportions relative to
total production and total seed use 79
11 Distribution of total basic grain production by
regions of Guatemala 83
12 Relative importance of the distribution of total
basic grain production by regions of Guatemala . . 85
13 Marketing expenditures as a percent of average
price received by enterprises and regions 91
x

LIST OF TABLES--continued
Table Page
14 Regression coefficients for each basic grain or
association by regions of Guatemala 94
15 Sign and significance level of the regression
coefficients for each basic grain or association
by regions of Guatemala 96
16 Income elasticities of market supply for each
basic grain or association by regions of
Guatemala 97
17 Area elasticities of market supply for each basic
grain or association by regions of Guatemala ... 99
18 Price elasticities of market supply for each basic
grain or association by regions of Guatemala . . . 101
A-l The price variable: descriptive statistics for
each of the estimated equations 163
A-2 The education variable: descriptive statistics
for each of the estimated equations 164
A-3 The total farm size variable: descriptive statis¬
tics for each of the estimated equations 165
A-4 The distance to market variable: descriptive
statistics for each of the estimated equations . . 166
A~5 The quantity demanded on the farm variable: de¬
scriptive statistics for each of the estimated
equations 167
A-6 The relative profitability ratio variable:
descriptive statistics for each of the estimated
equations 168
A-7 The total income variable: descriptive statis¬
tics for each of the estimated equations ..... 169
A-8 Rj corn-beans: simple correlation coefficients
matrix of the independent variables 178
xi

LIST OF TABLES--continued
Table
Page
A-9
A-10
A-l 1
A-12
A-l 3
A- 1
A-l 5
A-16
A-l 7
A-18
A-19
A-20
A-21
A-22
A-23
R corn-beans: simple correlation coefficients
matrix of the independent variables 178
corn-beans: simple correlation coefficients
matrix of the independent variables 179
R^ corn-sorghum: simple correlation coefficients
matrix of the independent variables 179
R^ corn-beans-sorghum: simple correlation coef¬
ficients matrix of the independent variables . . . 180
R. corn: simple correlation coefficients matrix
of the independent variables 180
R corn: simple correlation coefficients matrix
of the independent variables 181
R, corn: simple correlation coefficients matrix
of the independent variables l8l
R corn: simple correlation coefficients matrix
of the independent, variables 182
R, corn: simple correlation coefficients matrix
or the independent variables 182
R beans: simple correlation coefficients matrix
of the independent variables 183
R beans: simple correlation coefficients matrix
of the independent variables 183
R beans: simple correlation coefficients matrix
or the independent variables 184
R. sorghum: simple correlation coefficients matrix
of the independent variables 184
R^ rice: simple correlation coefficients matrix of
the independent variables 185
R rice: simple correlation coefficients matrix of
tne independent variables 185
xi i

LIST OF TABLES--cont¡nued
Table Page
A-24 R, rice: simple correlation coefficients matrix
or the independent variables 186
A-25 R. wheat: simple correlation coefficients matrix
of the independent variables 186
A-26 R, wheat: simple correlation coefficients matrix
or the independent variables I87
A-27 Regression coefficients for each basic grain or
association by regions of Guatemala 188
A-28 Income-quantity relationships for the associations
graphed in Figure 8 190
A-29 Farm size-quantity relationships for the associa¬
tions graphed in Figure 3 191
A-30 Price-quantity relationships for the associations
graphed in Figure 10 192
A— 31 Income-quantity relationships for corn graphed in
Figure 11 193
A-32 Farm size-quanty relationships for corn graphed
in Figure 12 194
A-33 Price-quantity relationships for corn graphed in
Figure 13 195
A-34 Income-quantity relationships for beans graphed
in Figure 14 1 96
A-35 Income-quantity relationships for rice graphed
in Figure 15 197
A-36 Farm size-quantity relationships for rice
graphed in Figure 16 1 98
A-37 Farm size-quantity relationships for wheat
graphed in Figure 17 199
x i i i

LIST OF FIGURES
Figure Page
1 Political divisions and transportation routes of
Guatemala b
2 Average wholesale prices for yellow and white
corn in Guatemala City, 1972-74 19
3 Average wholesale prices for black, white, and
red beans, in Guatemala City, 1972-74 23
4 Important crops in the different regions of
Guatemala 27
5 Guatemalan small farmer consumption and selling
decisions 58
6 Income-quantity or farm size-quantity relation¬
ships for the Guatemalan small farmer, given his
land constraint 83
7 Hypothetical production and distribution activities
for basic grains produced in the different regions
of Guatemala 71
8 Income-quantity relationships for the associations
by regions of Guatemala 103
9 Farm size-quantity relationships for the associa¬
tions by regions of Guatemala 104
10 Price-quantity relationships for the associations
by regions of Guatemala 105
11 Income-quantity relationships for corn by regions
of Guatemala Ill
12 Farm size-quantity relationships for corn by
regions of Guatemala 112
13 Price-quantity relationships for corn by regions
of Guatemal a 113
x (v

LIST OF FIGURES-~continued
Figure Page
14 Income-quantity relationships for beans by regions
of Guatemal a 117
15 Income-quantity relationships for rice by regions
of Guatemala 122
16 Farm size-quantity relationships for rice by
regions of Guatemala 123
17 Farm size-quantity relationships for wheat by
regions of Guatemala 127
18 Traditional and commercial income,farm size, and
price-quantity relationships in developing
agriculture 151
A-l Mathematical properties of the specified function . 171

Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy
TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE
IN AGRICULTURAL DEVELOPMENT:
THE CASE FOR BASIC GRAINS IN GUATEMALA
By
Jose Alvarez
June, 1977
Chairman: Chris 0. Andrew
Major Department: Food and Resource Economics
A growing population with about two-thirds employed in agriculture,
a limited arable land base, and poverty stricken farmers experiencing
unemployment and low levels of food production are character istics
that portray Guatemala as a developing country. The nation's develop¬
ment efforts focus on the implementation of programs designed to alle¬
viate those detrimental characteristics.
Program objectives at the Institute of Agricultural Science and
Technology (ICTA) of Guatemala intend to develop new technologies de¬
signed to generate productivity increases especially for basic grains
in the traditional farm sector. These programs will enable the country
to augment supply without expanding the area committed to production.
Two types of problems, however, may result from productivity
advances. Small farmers could use the new technology to produce the
xv i

same or even a reduced quantity of grains on less land. Or, if land
is fully utilized, "second generation" marketing problems are likely
to appear.
To avoid either type of problem, the investigation of traditional
and commercial supply response becomes of utmost importance. Accordingly,
the objectives of this study were to estimate market supply functions for
each basic grain or association (combined crops such as beans-corn) in
the different regions of the country; to compute income, farm size, and
price elasticities of market supply; and to delineate and quantify the
corresponding production and distribution activities. A model con¬
ceptualizing the small farmer's basic economic system was developed.
The surplus-output ratio was estimated as a function of the product's
farmgate price , education of household head, total farm size, distance
to the nearest market, quantity of the product demanded on the farm, a
relative profitability ratio, and total family income. Data used came
from a 197** Small Farmer Credit Survey conducted by the Guatemalan
government and the U.S. Agency for International Development.
Research results, from the input standpoint, show that basic grain
production is most influenced by seed and fertilizer costs. While
fertilizer use tends to be a generalized practice, with the level of
application depending upon crops and regions, pesticides and soil
additives are not commonly utilized. All enterprises present different
levels of employment by region except for the associations where labor
use per hectare is very similar.
xv i i

Total production differs among enterprises with respect to yields
and product distribution. Variations in cash sales are the result of
differences in farm demand for production and consumption purposes;
the more traditional the crop, the lower will be sales.
The results of the regression equations support the conceptual
model; in general, the estimated coefficients behave as hypothesized.
Traditional crops generally appear at near zero income and farm size
levels while commercial crops are cultivated when higher levels of
income and farm size have been attained. Elasticities of market
supply for traditional and commercial crops are high at low levels
of income and farm size. However, while commercial crops still show
some responsiveness at higher income and farm size levels, the tra¬
ditional crop response becomes almost perfectly inelastic, This
behavior is the result of farmers becoming involved in the activities
of the market economy once self-sufficiency has been secured, and
shifting into commercial crop production at higher levels of income
and farm size.
Thus, since traditional crops pervade the basic grains production
system in Guatemalan agriculture, little hope prevails for the attain¬
ment of massive increases in supply of basic grains. Although corn
in regions three and four and rice in regions four and five seem to
have a slight potential for increased production, the resulting in¬
creases would fall far behind the goal of the Guatemalan government.
xy 1.1 i.

CHAPTER I
INTRODUCTION
This chapter presents the problematic situation and the environment
within which this research project evolved. Some of the most important
agricultural and development related characteristics of Guatemala are
described, followed by the problem setting and the objectives of the
study. The importance of the project is discussed briefly. The data
source is explained, as are the important considerations concerning use
of the data in the present study.
Setting of the Study^
Although a developing nation sharing certain characteristics with
other Third World countries, Guatemala possesses unique characteristics
to differentiate the country from other nations. To better understand
the present study, some of Guatemala's most important physical, demo¬
graphic, economic, and social characteristics are described in this section.
Physical Environment
Guatemala, with an area of approximately 42,000 square miles (ex¬
cluding British Honduras or Belize, which Guatemala claims as its
This section
i s based on [24] .
1

2
territory), lies entirely within the tropics. It is bordered on the
north and west by Mexico, by the Pacific Ocean on the south, by El
Salvador on the southeast, on the east by Honduras and the Gulf of
Honduras, and on the northeast by British Honduras.
The climate ranges from hot and humid in parts of the lowlands
to very cold in the highlands. This wide range in climatic variation
permits the cultivation of any crop grown in the Western Hemisphere.
Landforms are also in great variety. The altitude varies from sea
level to over 13,000 feet in the volcanic highlands.
Rainfall occurs mostly from May to November and varies geograph¬
ically. The Caribbean coastal plain and adjacent areas receive the
heaviest annual rainfall, which may reach 200 inches. On the Pacific
side annual rainfall is less and diminishes toward the coast. Guatemala
City, in the highlands, averages about 45 inches of rain per year.
Population
Guatemala is the most populous country in Central America--4.3
million inhabitants according to the 1964 Census. The Guatemalan pop¬
ulation growth rate, one of the highest in the world, was approximately
3-1 percent per annum at the time of the 1964 Census. It is expected
that by 1980 the population of Guatemala will reach 7 million people.
Extremely high birth and death rates produce the consequent problems of
a young population with over half under 18 years of age.
The population is predominantly rural (66 percent of the population
according to the 1964 Census) and is concentrated in the highlands, where
the population density has greatly reduced the available land. In 1964,

3
the population density of the country, considered among the highest in
the Western Hemisphere, was 102 inhabitants per square mile.
In the 1950 and 1964 censuses the population was divided into two
groups: Indian and non-Indian or ladino. The first group encompasses
those of pure Maya Indian descent who continue to live much as their
ancestors lived several hundred years ago. The second group, in its
broadest context, comprises those neither belonging to an Indian com¬
munity nor wearing the traditional Indian dress and following Indian
customs. Since ladino is a cultural term, it may be possible for some¬
one who is accepted as a ladino in a rural environment to be classified
as an Indian in the urban milieu.
According to the 1950 Census nearly 72 percent of the population
over seven years of age was recorded as illiterate. This figure declined
to 63 percent in the 1964 Census, with almost 79 percent of the rural and
over 36 percent of the urban populations still illiterate.
Although Spanish is the official language and is spoken by a majority
of the population, over 40 percent of the population speaks a native
lanugage, with each township having its own dialect. Over 17 different
Indian languages and hundreds of township dialects create special prob¬
lems for the total integration of the population within the mainstream
of nationa1 life.
Government and Political Subdivisions
Guatemala is a Republic with three branches of government: executive,
legislative, and judicial. The Republic is comprised of 22 major polit¬
ical subdivisions (similar to states) called Departamentos (Figure l),
each Departamento being divided into a number of municipios (similar to

k
Figure 1
--Political
routes of
divisions
Guatema1 a
and
transportation
Source
[2k, p. xiv]

5
counties) of which there were 325 in 196^. The cabecera (capital of a
municipio is called either a pueblo (village), or a villa (large village),
or a ciudad (city) if it is also a Department capital. The municipio is
made up of a number of a 1 deas (hamlets) and caserTos (small rural commu¬
nities) and the cabecera of the municipio is divided into cantones (wards).
The Economy
Guatemala's Gross National Product (GNP) is the largest of the
Central American countries, reaching 1.5 billion quetzales in 1967 (one
dollar is equal to one quetzal). Although growing at an average rate
of 5 percent annually since 1950, the economy's growth has been erratic
with substantial fluctuations in the annual growth rate of Gross National
Product. Per capita income has been growing at a rate of about 2.5 per¬
cent since 1957; it changed from less than Q170 in 1955 to Q31^ in 1966.
Traditional farmers' annual income is estimated at about Q85-
Guatemala's economy encompasses three major sectors: domestic food
production, export crops, and industry. Construction and miscellaneous
services supplement the three main sectors. The Indian economy, predom¬
inantly subsistence agriculture, is largely self-supporting and regional.
The Indians are not completely integrated into the money economy and sur¬
plus production, when present, is usually bartered or sold in local mar¬
kets. I terns for which the Indians can not barter are purchased with
money earned during the harvest season by working for wages on planta¬
tions. Domestic crop production is characterized by its low level of
productivity as the result of primitive agricultural techniques and a
rigid land tenure system all of which sometimes require the importation
of food.

6
Much of commercial agriculture is managed by foreign firms, such
as fruit companies, the ladino aristocracy, and also by the Government.
The rapid development of export products such as coffee, cotton, sugar,
and beef contrasts with the stagnant characteristics of the domestic
food production sector, which has been unable to develop.
The industrial sector, although mainly concentrated in food pro¬
cessing, is rapidly expanding, having grown at an average annual rate
of 10 percent between 1961 and 1967- This growth rate was stimulated
by laws designed to grant tax benefits and by participation in the
Central American Common Market.
Agriculture
Agriculture is the dominant sector of Guatemala's economy. The
agricultural sector has accounted for more than 80 percent of all ex¬
ports since 1953; it provides about 30 percent of all raw materials
used by domestic industries; and the sector employs about two-thirds
of the population. Agriculture also accounts for about one-third of
GNP.
Major crops are corn, rice, wheat and beans and three major export
crops--coffee, cotton, and bananas. Minor export crops include essential
oils, tobacco, and honey. Crops primarily for domestic use include
rubber, cacao, fruits and vegetables, sorghum, millet, sesame, potatoes,
cassava, and hard fibers. Livestock and poultry are also important and
have grown rapidly in the last decade.
Agricultural activities take place within a very rigid system of
land tenure. Over 98 percent of the farms have an area under 100 acres

7
and occupy 28 percent of the land being farmed. On the other hand,
only 0.1 percent of the total number of farms are larger than 5,000
acres, but they occupy 41 percent of the farm land. In the 1950
Census, 1.3 million people 1ived on landholdings averaging 3-5 acres,
the minimum amount considered sufficient to satisfy the basic needs
of one family. In 1965, the situation was even worse; the Guatemalan
National Planning Council estimated that the number of landless fami¬
lies had increased by 140,000 and that over 90 percent of all rural
families were either landless or possessed insufficient land for sub-
sistence.
Markets and Marketing
Markets and fairs occupy a very important place in the life of
rural Guatemala. Each community holds at least one special market
day per week, which is a socio-economic institution. Although these
markets are the traditional response to the economic conditions of
Indian life, pricing is determined not by customs but by supply and
demand conditions. Sellers are mainly Indian women; buyers are both
Indians and 1 adinos. Products, ranging from food to handicrafts .
and clothing, are displayed by type and origin. Each township is
known for a particular commodity being less expensive than in other
markets. They may continue for several days and attract people from
all over the country.
Besides markets and fairs, marketing activities in the country¬
side take place in small general or neighborhood stores. These stores
are often located in the onwer's home. In larger towns, stores are of
a permanent structure and owners are professional merchants.

8
Guatemala City, the capital, possesses a large number of retail
stores, one large plaza market for each of 15 zones, a central market,
and a number of well-stocked supermarkets. The capital is also the
principal marketing and distribution center for all imports.
Marketing activities are severely handicapped by the bad quality
or lack of communication. Certain regions of the country still remain
relatively isolated (Figure 1). Much of the produce for domestic
trade is carried to the local market on the backs of men and mules over
dirt trails and footpaths.
Foreign Trade
Guatemala's foreign trade is characterized by a large number of
trading partners, a short list of commodities traded and for most years
an unfavorable balance of trade. Guatemala maintains commercial rela¬
tions with about 76 countries and is signatory to several international
agreements. The United States is Guatemala's primary trading partner,
although this share has been slowly decreasing. Coffee, cotton, sugar,
beef, and bananas are the main exports. Nickel and flowers are new
promising export products. Consumption goods are the primary imports.
In each year between 1957 and 1969, with the exception of 1966, Guate¬
mala experienced unfavorable trade balances which had to be financed by
credits and loans.
Agricultural products are the most important items of foreign trade.
Very low levels of grain production in Guatemala have forced the impor¬
tation of cereals and the consequent annual deficit in cereal trade
(Table 1). From 1963 to 1972, agricultural imports represented 13-^ to

9
Tabic 1.--Guatemala 1s imports and exports of cereals, 19^3“72
Year
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
-Mill
ions of
U.S.
Dollars
Imports
7.6
8.0
7-8
7-0
8.6
8.7
7-0
10.2
9.9
10.8
Exports
0.1
0.2
0.6
0.8
1.0
1.1
1.2
1.8
1.3
2.5
Oeficit
7.5
7-8
7.2
6.2
7-6
7.6
5-8
8.4
8.6
8.3
Source: [117, P- 84].

10
9.2 percent of total imports. Agricultural exports, on the other hand,
have represented between 69 and 88 percent of total exports during the
same time period (Table 2). For both imports and exports, agriculture's
share of trade had declined. Yet it is important to note the extremely
important role played by the agricultural sector's export surplus in the
overall trade balance situation for Guatemala. Over the 1963“72 period
this role increased as the share of agricultural imports of total agri¬
cultural trade declined from about 14 percent to 11 percent.
Setting of the Problem
Int roduction
The above description portrays Guatemala as a developing country.
Most of the character i s f i es descr i bed are common in other Third World
countries. First, the country's population, especially the rural pop¬
ulation, is growing rapidly. The Guatemalan population growth rate at
approximately 3.1 percent per annum is high. When the population of
Guatemala reaches a projected seven million people in 1980, 63 percent
of the economically active population will be employed in the agricul¬
tural sector. Compared with 65 percent in 196*1, this represents an in¬
significant decrease. Although employing 65 percent of the labor force,
agriculture only contributes about 30 percent to the Gross National
Product [35]•
Another characteristic common to Third World countries is that
Guatemala has a limited arable land base. Yet a large percentage of
privately owned land is idle as a result of the prevailing land tenure

Table 2.--Guatema1 a 1s agricultural imports and exports, total imports
and exports, and agricultural percentage of total, 1963-72
IMPORTS
EXPORTS
Year
Agricultural
Agricultural
\gr icul ture
Tota 1
percent
Agriculture
Total
percent
of total
of total
Mill ions of U.
o • uoi 13 r s
1963
22.9
171.1
13.4
135.2
154.0
87.8
1964
24.0
202.1
11.9
140.1
166.8
84.0
1965
25.2
229.0
11.0
156.6
185.8
84.3
1966
24.1»
206.9
11.8
185.4
226.1
82.0
1967
30.1
247.3
12.2
140.6
203.9
69.0
1968
29.1
249.4
11.7
164.4
222.2
74.0
1969
24.3
250.2
9.7
186.3
255-4
72.9
1970
31.5
284.3
11.1
200.9
290.2
69.2
1971
31.3
303-3
10.3
198.5
283.1
70.1
1972
30.0
327.7
9.2
234.8
328.1
71.6
Source: [117, pp. 52-9]-

12
system [2A, p. 260]. Nearly all arable land in the highlands is pre¬
sently under production. Government policies prohibiting tree removal
to bring new land into production in regions such as El Peten contri¬
bute to a land scarcity condition that is further aggravated by the
population situation.
A third characteristic, common to other Third World countries, is
that many Guatemalan farmers live in poverty conditions, are often un¬
employed and unemployable, and have very low levels of food production.
For example, net income per capita in the central highland region has
been estimated recently to be Q117 per annum [26, p. ^3]- In the same
area, real product per capita went from Q77 in 1951 to Q51 in 1966 [35,
p. 23]. A recent study conducted by the Institute of Agricultural
Science and Technology (ICTA) in the community of Santo Domingo Xenacoj
supports these figures [17]. The community, where family income averages
from Q90 to Q200 per year, is plagued by such a high unemployment rate
that part of its population is forced to migrate to cities and the
coast in search of new employment opportunities.
Successful efforts directed to solving population, employment, land
use, and income problems will benefit Guatemalan development. The imple¬
mentation of programs leading to more intensive land use, the reduction
of unemployment, and the increase in production and productivity in rural
areas ought to receive top priority among the country's development
efforts.
Agriculture, especially small farm agriculture, can play an important
role in Guatemala's march towards economic and social development. In
1951 a mission sponsored by the International Bank for Reconstruction and

13
Development reported that "it is clear that any appreciable rise in
Guatemala's standard of living can come only through improvements in
agriculture" [51, p- 27]. Several researchers have suggested that
programs to improve agriculture should be oriented toward small rather
than large farmers because small farmers utilize scarce resources more
efficiently in food production [19, 35, ^7]. Furthermore, the contri¬
bution of the traditional small farmer to overall production, especially
basic grains production, is relatively large. Fifty-five percent of
total basic grains production in the country comes from farms under
seven hectares. Waugh states that it is evident that the small farmer's
production is of first order of importance to the country. He goes on
to say that this production results from a very limited percentage of
the land in farms and that 67 percent of the total number of farms in
the size group 1.7 to 7 hectares have only 18 percent of the total land
in farms [ 118, p. 2]. Furthermore, it is in the small farm sector where
economic and social development are most needed.
Certain characteristics of Guatemalan agriculture necessitate pro¬
gram formulation at the subsector level. Fletcher £t_aj_, [35, pp. 51, 53]
identified three subsectors in Guatemalan agriculture: the traditional
agriculture of the highlands (corn, beans, wheat) and other parts of the
country; export crops (coffee, cotton, and bananas); and commercial agri¬
culture mainly for domestic consumption (the majority of the remaining
crops). Since these subsectors face different produce demand schedules
and marketing problems, agricultural development programs wi11 be most
successful when formulated at the subsectoral level. Accurate problem
identification leading to specific solutions for each subsector would

u
then be easier. This study is mainly concerned with the traditional
(subsistence) and commercial subsectors of Guatemalan agriculture. A
distinction ought to be made between traditional and commercial farmers,
2
and between traditional and commercial crops. The term traditional
farmer does not necessarily include only Indian pre-Colombian types of
agriculture; it is also used to signal farmers who historically ignore
market stimuli and are not prepared to shift from one crop to another;
they can not respond easily (neither economically, culturally, nor
technologically) to stimuli. In general, the term traditional means
any system which has been used for "a long time" and has not been
"modernized" particularly in the use of petroleum based products. Al¬
though these farmers may use some fertilizer in some regions (where
water is available), they apply almost no insecticides (ownership of a
sprayer means an additional investment). The commercial farmer is
price responsive and has the means to shift between crops; his farming
is a business and he responds to market stimuli.
The difference between traditional and commercial crops is based
on the destination of the product and the utilization of labor in its
production. In traditional crops, farmers tend to use about 80 percent
family labor and 20 percent contract or hired labor, and, although some
output may be sold when a surplus occurs, production is mainly devoted
to family consumption. In commercial crops the characteristics are
2
The discussion is based on personal communication with Peter E.
Hildebrand, Coordinator, Socioeconomics Program, ICTA-Guatemala.

15
almost exactly the reverse. These sharp distinctions among subsectors
validate the assertion concerning the necessity of formulating programs
at the subsectoral level.
Work at the Institute of Agricultural Science and Technology (ICTA)
of Guatemala is focused on subsectoral problems. On January 20, 1976,
the Minister of Agriculture of Guatemala announced that the government
was launching a program to increase agricultural production with special
emphasis on basic grains [22, p. 1]. Accordingly, ICTA's 1976 plan com¬
prises production programs for different agricultural products (corn,
beans, rice, wheat, sorghum, vegetables, and hogs) with the support of
disciplines such as Soil Management and Rural Socioeconomics. The crea¬
tion of the Program of Rural Socioeconomics is the result of ICTA's
policy based
... in the belief that an appropriate technology can only
be developed through the study of the causes conditioning
the application of new technologies and this is achieved
by means of agro-socioeconomic
stud ies
at
the
farm
level
in continuous contact with the
farmer
who
wi 1 1
be
i ts
principal usufructuary. Therefore, the contribution of
the socialsciences(Economics, Sociology, Anthropology),
is the key which will enable us to know these causes and
will permit the recommendations to be based on the agro¬
nomic research and correspond to the requirements of the
environment to which they are intended...[53, P- 217]-
Problem Statement
ICTA's subsectoral programs are intended to develop a new tech¬
nology based on the environment in which farmers live, to generate
productivity increase that make it possible for Guatemala to supply
its growing population with more agricultural products per capita
without an increase in the area used in production. For example,

16
several diseases and weeds affecting corn have been controlled and,
by utilizing a new seed variety, yield per acre in La Máquina, located
in the Suchitepequez Department, can be doubled and even trebled.
Another example pertains to research on interplanting beans with corn
and on insecticides and new seed varieties that will eventually lead
to larger bean yields. Research on wheat is seeking new seed vari-
ties with high productivity and resistance to primary diseases and
adapted to different regions of the country and small farmer use.
The new wheat variety, "Gloria", introduced in the Cooperative Santa
Lucía, R.L., has' doubled wheat production and has been accepted by
the farmers of the area [52]. Since the new technology is being de¬
veloped considering the conditions and limitations that farmers face,
farmers are making full and best use of the technology.
The adoption of the new technology, it is hoped, will foment
increases in production and productivity. In Guatemala, as in most
developing countries, a large portion of agricultural production is
consumed on the farm. Thus, the adoption of new production techniques
may arise from the desire to sell the extra production for cash. Very
little is known, however, about the intensity of marketing and consump¬
tion problems that must be faced if farmers market most of the increase
in output.
An increase in marketed output may intensify the strong tendency
towards price instability inherent in the marketing of agricultural
products. Abbott attributes instability to the seasonal concentration
of output, great difficulties in adjusting production closely to demand

17
in view of the uncertainties of weather and yields, and to the rela¬
tively low price elasticities of demand for the basic food products
[2, p. 6].
Productivity advances can also show how rapidly the so called
"second generation marketing problems" can arise. Falcon, when
writing about the Green Revolution, expressed his hope that decision
makers in the future will heed the warnings earlier of marketing spe¬
cialists and will react before critical product distribution situa¬
tions develop [32]. Such problems range from the early identifiable
problems related to drying, storing, transportation, etc., to the
less identifiable, but not less important, problems of pricing and
markets. It is extremely important to face these problems on a
timely basis, avoiding the erroneous belief that marketing is an
accomodating, spontaneously generated activity that can be somehow
performed once production has been increased. The following research
is addressed to more fully understanding the differences in supply
response in the traditional and commercial subsectors due to changes
in agricultural technology.
Market problems in the future will combine with those at present
such as unstable agricultural prices, the absence of adequate marketing
channels for both inputs and outputs, and the lack of knowledge concern¬
ing demand and supply relationships. The vast importance of corn to the
national economy and, in particular, to small farmers in the highlands
has been documented [98], yet it is surprising how little information
related to corn marketing is available. For example, there are no com¬
plete and reliable data for corn moving through the different marketing

18
channels. The lack of drying and storing facilities causes concern to
government officials, wholesalers, and farmers. Surveys conducted by
the Agricultural Marketing Board reveal substantial differences in
losses during marketing among the different zones of production due
to differences in storage, transportation and processing. Fletcher, et al .
say that the majority of the important problems prevailing in corn
marketing are related to the lack of adequate facilities for drying
and storing [35» P- ^3], which causes substantial losses and produces
considerable variation in the price of corn (Figure 2 and Table 3 to
Table 5). The variability in the price of corn may benefit those who
can store large amounts of corn for three to six months, but neither
helps the small farmer who needs cash at the time of harvest nor the
consumer who buys this product in small quantities. The same phe¬
nomenon prevails in bean marketing (Figure 3 and Table 3 to Table 5)•
Price stabilization for corn and beans, therefore, is an important
objective of the Guatemalan government.
The need for conducting supply and demand studies in the rural
areas is evident. An important aspect on the demand side is the quan¬
tity of basic grains that small farmers demand. Since much of their
(
production is consumed on the farm, knowledge of their demand is needed
to estimate the future amounts of basic grains they will send to the
market as a result of increased production. Since the nature of the
available data does not permit the identification of demand functions,
this research will be focused mainly on supply.

Quetzales per Quintal
Figure 2.--Average wholesale prices for yellow and white corn in Guatemala City ,1312~lb
Source: [55, 56].

20
Table 3-—Average wholesale prices for beans and corn, in Guatemala
City, 1972
Month
Black
Bean
Wh i te
Bean
Red
Bean
Yellow
Corn
Wh i te
Corn
A , I
uuetzaies per
is*u i n ta i — —
January
7.77
10.08
7.47
2.90
2.73
February
—
—
—
—
—
March
7.85
10.14
7.65
2.82
2.64
Apr i 1
7-50
9.96
7.58
2.74
2.89
June
—
—
—
—
—
July
7.18
11.00
7-58
2.80
2.90
August
9.12
12.01
9.06
3.22
3.22
September
9.10
12.44
9.92
3.22
3.33
October
9.16
12.14
10.30
3.42
3.07
November
10.75
12.69
11.31
3.83
3.77
December
13-35
11.86
14.98
4.95
4.95
Source: [55, 56].

21
Table 4.--Average wholesale prices for beans and corn, in Guatemala
City, 1973
Month
Black
Bean
Wh i te
Bean
Red
Bean
Yellow
Corn
Wh i te
Corn
__ _ .. _ n i ~^ ^ ^
January
11.15
13.08
11.73
4.79
4.80
February
12.08
13-53
12.73
4.91
4.94
March
13-75
14.23
13-48
5-14
6.07
April
12.47
14.56
13-46
6.50
7.23
May
12.35
14.67
13-73
6.42
7.02
June
14.85
17.84
15.88
6.07
6.61
July
14.33
19-35
16.80
5.87
6.46
August
10.60
15.93
11.97
5.29
5.62
September
12.36
15-00
12.99
4.92
5.18
October
15-48
15.19
14.05
5.59
5.25
November
18.24
15.03
14.63
6.55
6.16
December
17-08
15.20
15.34
6.46
6.08
Source: [55]

22
Table 5---Average wholesale prices for beans and corn, in Guatemala
City, 197**
Month
Black
Bean
White
Bean
Red
Bean
Yellow
Corn
White
Corn
â– Quetzales per
i n La 1 — — —
January
16.39
1*4.90
15-35
6.22
5.98
February
16.13
15-00
15-38
6.13
6.01
March
16.61
16.*4 *4
16.83
6.90
7.07
April
15.53
15.58
15-91
7-77
7.97
May
16.09
15-90
16.80
7.03
7.09
June
16.86
16.72
17.53
6.70
6.60
July
17.88
17-79
18.*4 *4
6.72
6.56
August
1*4.87
15.5*4
1*4.76
6.*46
6.25
September
15.21
15.33
15.03
6.62
6.51
October
17-77
16.06
16.03
6.*48
6.30
November
19.78
18.02
17.82
6.65
6.*4 *4
December
19-0*4
18.33
18.33
6.88
6.78
Source: [55]

20
19
10
17
16
15
14
13
12
11
10
9
8
7
1972
1973
1974
YEAR
:igure 3.""Average wholesale prices for black, white, and red beans, in Guatemala
City, 1972-74
M
Oo
: [55, 56].

2k
On the supply side, detailed market knowledge and research on
where, when and for what price products can be sold is essential in
determining what to produce. Due to very large seasonal and cyclic
fluctuations in the prices of agricultural products, farmers in de¬
veloping countries rationally choose to grow sufficient food for
home consumption. Market supply functions are important in deter¬
mining how responsive farmers are to price, income and other variables
for policy decisions aimed at securing adequate increases in the mar¬
keted supply of food crops. Since the responsiveness will be different
in different milieus, elasticities of supply must be estimated separately
for different regions. Market supply functions may also signal possible
future changes in land utilization. It has been observed very recently
in the communities of San Martin Jilotepeque and El Novillero that, as
the small farmer obtains a better standard of living resulting from
new corn technologies, there is a tendency to reduce the amount of
land devoted to corn production since this is mainly cultivated for
family consumption [107].
Knowledge of the characteristics of production and distribution
activities is needed. Their description and quantification, especially
in the market for inputs, will show cost and availability of inputs in
each region. Comparing results with actual output in the region may
provide a basis for identification of problems that can be solved by
policy decisions. In a marketing study of basic grains, the Institute
of Agricultural Marketing (INDECA) delineated the marketing channels
for these products [5*0- The study lacks, however, the corresponding

25
data for each channel and therefore it is impossible to know the relative
importance of each channel; it also contains no information about the
movement of inputs to small farmers.
There is no doubt that the existing problems and those that will be
generated by the increase in production and productivity of basic grains
require careful study to avoid the imminent "Green Revolution" second
generation problems. Knowledge of total supply and marketed supply
functions, production and distribution activities, and the behavior of
the surplus-output ratio as income and farm size change, is important
in solving present problems and in trying to avoid major market problems
in the future. It is in this context that the following objectives are
undertaken.
Objectives of the Study
The objectives of the study are to:
1. Estimate market supply functions for basic grains in the
different regions of the country and compute the corresponding
income, farm size, and price elasticities of market supply.
2. Delineate and quantify input acquisition and product dis¬
position for basic grains in the different regions of the
country.
Data Source and Data Considerations
The data are derived from the Small Farmer Credit Survey conducted
by the Government of Guatemala and the Agency for International Develop¬
ment (AID) in 197** for agricultural activities during the 1973 calendar

26
year. These cross section survey data contain necessary and valuable
information for conducting this research since time series data are
completely unavailable. The overall objective of the survey was to
compare the performance of small farmers receiving credit from the
government with non-recipients. A sample was selected by sub-region
in order to have a minimum number of sample farms producing the desig¬
nated main crop for each sub-region. Interviews were taken with 800
pairs of farms, from which a total of 1,5^3 questionnaires were com¬
pleted.^ Figure A shows the different regions with their respective
important crops. Table 6 and Table 7 present the number of sampled
farms and farm size by region, sub-region and department, respectively.
By reviewing Figure 1, it becomes evident that the survey reached every
Department in the nation, except El Peten (Region two) which is a semi-
isolated area in the process of colonization.
A word of caution about the representativeness of the data is appro¬
priate. The no-credit farmers viere selected because of their similarity
in age, size of farm, crops grown, etc., to the group of farmers receiving
credit. Therefore, the former group would represent all farms in
Guatemala only to the extent that the latter group does. Interest how¬
ever falls in drawing conclusions about traditional and commercial agri¬
culture at the regional level. In this case the sample does contain
enough farms engaged in either or both types of agriculture such that
conclusions by farm type at the regional and national levels are possible.
^Complete descriptions of the sampling procedures are available in
[19, 106]. More information about the survey's results is contained in
[75, 92, 101].

27
Figure AImportant crops in the different regions of Guatemala
Source: [19, P- 1*»]

28
Table 6. — Number of sampled farms by region and farm size
Farm
S1 ze
i»cy l vji i
0-0.9
Ha.
1-2.9
Ha.
3-4.9
Ha.
5-9.9
Ha.
10+
Ha.
All SIzes
1 Central Highlands
64
1*5
75
56
40
CO
o
3 South Coast
5
10
14
14
59
102
(West)
4 South Coast
7
68
49
75
89
288
(East)
5 Northeast
28
151
86
83
134
482
6 Southeast
HIghlands
9
77
75
59
76
296
National Totals
113
451
299
287
398
1548
Source: Computed from [19, p. 20]

29
Table 7.__Number of sampled farms by region, sub-region,and department
Region
Sub-Region
Department No.
Department Name
No. of Observations
1
1
13
Huehuetenango
96
2
12
San Marcos
48
2
9
Quezaltenango
52
3
9
Quezaltenango
1
3
Ik
Qu i che"
40
3
8
Tonton i capa"n
23
3
7
So 1 a 1 a”
30
it
i*
Chimaltenango
54
4
3
Sacatepéquez
36
380
3
5
12
San Marcos
32
5
11
Retalhuleu
49
5
10
Suchitepequez
21
102
4
6
5
Escuintla
50
7
5
Escuint1 a
91
6
10
Suchitepequez
45
6
3
Sacatepéquez
1
7
k
Chimaltenango
1
8
6
Santa Rosa
84
8
21
Jalapa
5
8
22
Jut i apa
11
288
5
9
16
Alta Vera Paz
89
9
6
Santa Rosa
1
9
15
Baja Vera Paz
4
10
15
Baja Vera Paz
78
10
14
Qu icbe
16
10
10
Suchitepequez
4
11
19
Zacapa
81
11
2
El Progreso
19
12
2
El Progreso
30
12
1
Guatemala
64
13
18
Izabal
96
482
6
14
22
Jutiapa
98
15
21
Jalapa
77
15
6
Santa Rosa
19
16
20
Chiqui mu 1 a
102
296
Total 1548
Source: [19].

30
George and King's arguments in support of the use of cross-section
data in their research [37] can be extended to the present study. First,
time-series data are not available; but even if they were, more reliable
(demand) parameters can be estimated with cross-section data. In static
analysis, a (demand) relationship is specified for a particular period
of time. In practice, as George and King point out, [37, pp. 28-9] each
time an observation is made, we get one point on a (demand) curve and,
by the time another observation is made, the curve might have shifted
because one or more factors influencing (demand) may have changed.
These shifts may influence the nature of functions obtained from time-
series analysis and, at times, it will be difficult to isolate the
effects of such shift variables from purely economic variables such as
prices and income. Thus, wrong conclusions about the non-significance
of economic variables in explaining (demand) could be drawn.
Second, since prices generally remain unchanged during a short
period of time, cross-section data make it possible to estimate income
elasticities free from price effects. George and King state that cross-
section data primarily reflect the (demand) pattern in the sense of
long-run income changes so that the income elasticities computed from
these data can be interpreted as long-run elasticities. From the point
of view of practical applications of (demand) analysis, these long-term
elasticities are more relevant for many policy decisions than the short¬
term elasticities obtained from time-series data.

31
Relevance of the Project
Income and farm size elasticities of market supply are important
determinants in signaling farmer behavior concerning potential increases
in quantities produced and marketed and in land utilization. These elas¬
ticities permit the estimation of the effects that may result from future
increases in productivity and production, if in fact they occur, and in
income. Price elasticity may also be computed but would be less mean¬
ingful due to the nature of the data. Price observations from the cross-
section data available do not capture seasonal prices because interviews
were taken at one time due to research resource constraints. The aggre¬
gate prices taken can create price elasticity situations without easy
interpretation and application. This drawback, however, appears to be
less relevant as emphasis is given to the income and farm size elastici¬
ties and the income-quantity and farm size-quantity relationships as
indicators of farmer supply responsiveness to factors that change his
income and farm size.
One of the most important implications of testing the theory pre¬
sented in this study is obtaining a better understanding of the basic
economic system of small farmers and the relationships between this
system and Green Revolution agriculture. The theory suggests that there
is a built-in supply control mechanism for basic grains and low value-
low risk crops in the small farm system. This mechanism, explaining why
productivity increases yet production is stagnant, is a natural reaction
to basic subsistence needs and avoids some of the second and third gen¬
eration problems of the Green Revolution [32]. Overproduction may not

32
usually result so prices would not decline sharply to create great income
disparities and the usually disoriented market system itself would not be
so forcefully challenged.
Should these hypotheses prove reasonably accurate, research and de¬
velopment programs might carefully consider the total small farm system.
Basic research on basic grains alone will not serve the small farmer's de¬
veloping needs entirely as he moves into higher value-higher risk crops.
Meeting the risk element squarely in both agronomic and economic research
programs might be most productive.
Organization of the Dissertation
The setting of the study, with its problematic situation and impli¬
cations, has been presented in this chapter. The theoretical framework
of the second chapter describes the role of agriculture and of marketing
in economic development, with special emphasis on the theory of demand
and supply in LDCs. After the theory and literature are reviewed, the
methodology used in accomplishing the objectives is presented in the
third chapter. The fourth chapter describes input acquisition and pro¬
duct disposition for basic grains in the different regions. Chapter five
encompasses both the results and the corresponding analysis, and the
sixth chapter contains a summary, the conclusions, and recommendations
based on the results obtained. The final chapter, "Reflections on the
Theory of Development," is an attempt at actualizing the current develop¬
ment literature of the second chapter in light of the findings in chapter
five.

CHAPTER I I
AN EVOLVING THEORY OF AGRICULTURAL DEVELOPMENT
That part of the development literature related to agricultural
development and marketing Is summarized In this chapter. The rela¬
tionships between agriculture and economic development are the subject
matter of the first section. The second section describes marketing
activities and their role in the development process with special
emphasis on the theory of demand and supply In developing countries.
Agriculture and Economic Development
Since World War II the literature has paid increasing attention
to the process of economic development in the developing countries.
There seems to be a consensus on the need for sustained growth to
bridge the gap that separates LDCs from the industrialized nations.
Though the problem of an overall development strategy is continually
discussed, the key role that the agricultural sector has to play is
today widely accepted. In this chapter, some of the most important
viewpoints, especially those related to the problematic situation
described above, are analyzed.
33

34
Agriculture in LDCs: A Changing Spectrum of Priorities
Arthur Gaitskell [36, pp. 46-50] has tried to explain why agricul¬
ture until recently has experienced a very low priority in developing
countries. He enumerates the following reasons:
(a) Since the richest countries in the world are the industrial
countries, it seemed logical that industry, rather than
agriculture, was the means for development.
(b) Developing countries have been sources of raw materials
for the industrialized nations and a market for their
manufactured products, but their terms of trade have
been deteriorating. Developing their own industries,
therefore, seemed to be a correct goal.
(c) Private foreign investment was, for a long time, the
pattern of development without any national participation.
(d) Traditional values ("not everybody gives development top
priority in their lives"): Leisure, status, religious
precepts, traditional methods of ancestors, etc., played
an important role in hamper ing agricul tural development.
(e) Decision makers in LDCs come from the educated-elite and
they are fundamentally urban oriented.
(f) Other reasons favoring industrialization were: it has a
greater appeal than agriculture to LDCs since it suggests
the modern world. Machinery can be imported; it is easy
to learn how to use it and see the results. Agriculture
on the other hand is old and most people think they
already know all about it. Industrial output is less

35
uncertain than crops. Since a minority is engaged in
agriculture in the industrial countries, industry seemed
the obvious target for which to aim. Finally, since in
the most developed countries, industry's surpluses have
been used to pay for subsidies, a cause for technological
success, the idea of developing industry first found
greater appeal.
There has been, however, a recent shift to complementary growth of
agriculture and industry. Gaitskell [36, pp. 50-6] attributes the atten¬
tion given to agriculture to several facts:
(a) The existence of undernourishment and poverty is today a
main purpose for encouraging development. Since the main
areas affected are the rural areas, it follows that agri¬
culture has to be developed.
(b) The "left-outs" from rural areas constitute a serious
threat to existing political regimes.
(c) Industrialization alone can not solve the unemployment
problem since it is capital intensive.
(d) Foreign exchange earnings from agriculture are necessary
to buy the basic imports needed for industrialization.
(e) The increasing need for food as population increases
and land becomes even more scarce.
The time has come for proper priority to be given to progress of the
agricultural sector in developing countries where resources are favorable
and population growth is pressing.

36
Agriculture versus Industry: A False Issue
The issue of establishing development priorities in LDCs is of
utmost importance. In the process of making a choice, economists
have embraced one of two opposing views: those recognizing that top
priority should be given to increase food supply, and those advocating
a "big push" industrialization program. Among the advocates for the
first group are A.E. Kahn, J. Viner, Coale and Hoover, and others,
while A.Hirschman, Liebenstein and Higgins, among others, belong in
the second group. Heady [A6, pp. 66-7], though recognizing that there
is no univeral rule for making a choice between the two, outlines
several cases in which a choice can be appropriately made in either
direction according to specific circumstances. Nicholls [89, p. 16]
believes that the choice is a matter of degree and not of kind, and
states that there is probably no developing country in which it is
feasible to concentrate all of its investment on either agriculture
or industrial development, and it will be impossible to concentrate on
industry until a reliable food surplus has been achieved and sustained.
Since in most LDCs there is still a large agricultural majority coupled
with large rates of population increase, Dovring [27, p. 95] wonders
how large the rate of industrizalization must be to absorb the annual
increments in the labor force and reduce the existing surplus in agri-
culture.
Meier's comments on the issue seem to summarize very well the
current status of the debate:
The attainment of a proper balance between the establish¬
ment of industries and the expansion of agriculture is a per¬
sistently troublesome problem for developing nations. In

37
earlier discussions of development priorities, deliberate
and rapid industrialization was often advocated. Experience,
however, has shown the limitations of an overemphasis on
industrialization, and it is increasingly recognized that
agricultural progress is a strategic element in the develop¬
ment process. Industrial development versus agriculture has
become a false issue, and the concern now is rather with the
interrelationships between industry and agriculture and the
contribution that each can make to the other. It has also
become apparent that the relative emphasis to be given to in¬
dustry and agriculture must vary according to the country
and its phase of development [80, p. 285].
The Role of Agriculture in Economic Development
Papanek [93, PP- 289-91] advances several economic arguments for
heavy emphasis on development of the agricultural sector. The arguments
apply to the commercial and large scale (capital intensive) farms. First,
it is necessary to free labor for industrial development. Second, agri¬
cultural production can be raised rapidly and with little capital (pos¬
sibility of doubling crop production, or raising crops in previously
uncultivated areas, fertilizer use, improved seeds, etc.), while indus¬
trialization requires time and capital, skilled workers, managers, social
overhead capital and the like. Third, while the development of the
agricultural sector is capital-saving in requiring minimum expenditures
for overhead costs by obviating massive population movements, industria¬
lization would require heavy expenditures to provide at least minimal
facilities to the new city inhabitants. Fourth, development of agri¬
cultural production also is often the fastest method for decreasing needed
imports or increasing saleable exports in countries needing and lacking
foreign resources. Fifth, structural changes may be needed before
technical improvements in agriculture can be carried out without prior

38
industrialization. Finally, increased incomes will produce increased
demand for food and clothing. Agricultural production or imports wi 1 1
have to be increased as part of the development process since reinvest¬
ment of all of the increased production can not be expected.
The five propositions stated by Johnston and Mel lor [58, pp. 291 -
7] about the ways in which agricultural development, especially large
scale agriculture, contributes to over-all economic development follow
directly from the former arguments. First, economic development is
characterized by a substantial increase in the demand for agricultural
products, and failure to increase food production in pace with the
increase in demand can seriously impede ovei—all economic development.
Second, agricultural exports may provide foreign exchange earnings.
Third, the labor force for the expansion of the industrial sector can
contribute the capital required for overhead investment and expansion
of secondary industry. And, finally, rising net cash incomes of the
rural population may be important as a stimulus to industrial expansion.
There is no longer any doubt, according to Schultz [108, p. 5],
whether agriculture can provide a tremendous stimulus for over-all
economic development. It is only necessary to invest in agriculture
and, above all, to provide farmers with incentives. Once there are
investment opportunities and efficient incentives, as he puts it,,
farmers will turn sand into gold.
The role of agriculture in economic development according to
Nicholls [89, pp. 11-3] depends heavily upon the particular historical
circumstances of the country and upon the ratio of agricultural land
to population. The relative emphasis which decision makers give to

39
agriculture, and the consequent policies must therefore vary accordingly.
But it is clear for him that, either for an open or closed economy, the
agricultural sector can make tremendous contributions to over-all eco¬
nomic development and that, within considerable limits at least, the
development of this sector is a sine qua non before a take-off into
self-sustained economic growth can become a reality.
In many countries, however, agriculture has failed to respond for
what Heady [46, pp. 63-4] calls obvious reasons. First, agriculture
has not been given an appropriate priority. Second, there is a lack
ofa.price structure conducive to the use of new and more capital re¬
sources such as insecticides, fertilizers, and improved seed varieties.
Third, input prices have been kept too high and output prices have been
kept too low. Fourth, capital has not been moved into the hands of
subsistence farmers to incorporate them into the market economy. Fifth,
frequently, the absolute supply of and the facilities to move and store
inputs are lacking. To eliminate those adverse factors, several eco¬
nomists have suggested different prescriptions.
Some Prescriptions for Agricultural Development
Many sophisticated models have been provided for developing the
agricultural sector in LDCs. Except for Heady and Lewis, all of the
authors call for increasing employment on farms rather than replacing
labor with mechanized technology.
For Heady [46, p. 61] there is no mystery in the process of ex¬
plaining the development of agriculture. It is so simple that no new
theory is required. He proposes the following "recipe":

40
Lower prices and increase availability of resources,
add certainty and greacer quantity to product prices, blend
with knowledge and a firm or tenure structure which relates
input productivities appropriately with resource/product
price ratios. This mixture can be brought to a develop¬
mental boil in a container of commercial farming, if not
successfully in a purely subsistence environment which is
outside the market economy. It will have a delayed or
lagged maturity, depending upon the dosage of the above
variables and the extent to which a very few specific
cultural factors exist. These factors include (1) creating
a new "state of mind" for cultivators who have previously
been oriented to production best guaranteeing food for
subsistence in the year ahead, and who must now look to
expansion towards the market, and (2) acquainting families
with the mysteries of managing credit and capital in order
to convert them from subsistence operations.
This recipe has been tested and proven successful over
many parts of the world: so much that it is doubtful that
anyone will ever come up with a better one. Hence, the
creation of the conditions implied above is one of the
priorities for bringing economic development to agri¬
culture. There is no mystery to the process. If a
mystery exists, it is to explain those exogenous condi¬
tions which prevent governments and planning agencies, which
wish agricultural development, from manipulating the above
instruments and going forward with the recipe [46, p. 63].
Lewis' well-known article on "Economic Development with Unlimited
Supplies of Labour" [74] deserves special consideration. According to
him, in most developing countries the supply of labor is perfectly
elastic at current wage rates. The existence of disguised unemployment
in the agricultural sector, with zero or even negative marginal pro¬
ductivity, provides the basis for economic development. As workers
are absorbed by the industrial sector, capitalists earn a surplus, the
surplus can be invested with the resulting increase in marginal produc¬
tivity and, therefore, growth. Despite the controversy that followed
publication of this position, the article exerted tremendous influence
in the 1950's and 196O1s.

Premature displacement of labor from agriculture, however, could
hamper economic development. The demand for food (determined largely
by population growth and by the income elasticity of demand for food)
and the existing high rates of population growth with the difficulty
experienced by the urban sector to absorb this growth, yields the
Johnston and Mel lor policy prescription of
...a labor-intensive approach with reliance on yield-in¬
creasing technical innovations in the earlier phases of agri¬
cultural development. This policy approach produces the
required increases in agricultural production and avoids
displacing labor prematurely from agriculture. It is a pre¬
scription for agricultural research, for large increases in
the use of yield-increasing inputs such as fertilizer, im¬
proved seeds, insecticides and pesticides, for increases
in irrigation facilities and for building service institu¬
tions in extension, marketing, and credit. It is also a
prescription to minimize mechanization, especially when it
serves to displace labor [26, p. kS]•
Dorner [25, pp. 268-72] also points out important areas in which
policy changes could strengthen economic development and the status
of the small farm subsector. Of special interest to our case are:
First, development and introduction of new technology to increase
employment and production, with special emphasis on land saving tech¬
nologies if both increased production and employment objectives are
to be served. Second, modification of rural service structure to
assure access by small farmers.
No matter the prescription followed, it is essential to remember,
as Hirschman states, that "... development depends not so much on
finding optimal combinations for given resources and factors of pro¬
duction as on calling forth and enlisting for development purposes
resources and abilities that are hidden, scattered, or badly utilized"

[48, p. 5]• And that "th ere are always and everywhere potential sur¬
pluses available. What counts is the institutional means for bringing
them to life...for calling forth the special effort, setting aside the
extra amount, devising the surplus" [95, P- 339] •
Marketing and Economic Development
A negative feature of pricing systems in developing countries is
the existence of extremely high prices at the retail level restricting
consumption along with extremely low prices at the producers' level
which do not stimulate farmers to grow and market more products. There
exists no doubt that inefficiency in the marketing of agricultural pro¬
ducts is characteristic of most developing countries. Despite the im¬
portance of well organized and efficient distribution systems, the
study of the role of marketing in LDCs began only two decades ago.^
The purpose of this section is to profile the important role that mar¬
keting plays in economic development.
Marketing Defined
Marketing may be defined in several ways. In a broad sense, mar¬
keting can be identified as "part of the production process that assures
market outlets for farm products and makes readily available supplies of
production inputs which reduce price uncertainty and risk" [115, p. 1].
Abbott [2, p. 364] affirms that the first to point out specifi¬
cally the importance of marketing in economic development was R.H.
Holton in the beginning of the 1950's.

43
In a conference about marketing problems in LDCs [66, p. 6], agri¬
cultural marketing is considered to consist of four specialized areas
or activities. The first area, "factor marketing", encompasses the
functions of providing inputs for farming. The second is the movement
of commodities to consumers. The third area is concerned with the acti¬
vities performed by the processor converting the commodities into pro¬
ducts. The fourth is related to the export of the commodity.
Marketing operates in a certain environment and is affected by
different forces. Technology is, in our case, the most important factor
to consider. "Technology puts pressure on a marketing system to which
it must adjust, and similarly, technology has much to do with the pro¬
ducts distributed and their eventual acceptance" [49, p. 2]. Reynolds
[100, p. 154] says that marketing is affected by technological change
in three ways: by change in goods and production methods, by changes
in the ultimate consumer, and by changes in marketing itself.
The Role of Marketing in the Economy
An AID publication [67,pp. 27-8] lists three broad functions that
the marketing system performs in the economy. First, it performs the
reciprocal function of providing an outlet for producers and commodities
for consumers (household and processing firms). Second, it provides a
livelihood for those performing the different marketing activities, and
should yield reasonable returns to the capital and managerial abilities
devoted therein. Third, it signals those engaged in the production,
distribution, and consumption of commodities the actions they should
take in their own interest.

The importance of marketing can be appreciated in the triple
functions enumerated by Drucker [28, p. 335]: the function of cry¬
stallizing and directing demand for maximum productive effectiveness
and efficiency; the function of guiding production purposefully toward
maximum consumer satisfaction and consumer value; and the function of
discrimination, rewarding to those who really contribute excellence,
and penalizing those who do not want to contribute or to risk.
The economic aspects of marketing, according to Holloway and Hancock
[49, p. 1], are twofold in importance: First, consumer's behavior is
influenced by their economic status which creates an environment for
other influences to act upon the consumer. Second, firms act in the
market in a competitive atmosphere with price serving as a signal to
exchange transactions. "In this way the economic dimension is broadened,
and the economic environment of the firm becomes a market force worthy of
consideration" [49, p. 1].
The Role of Marketing in Economic Development
Marketing is an essential consideration when planning economic de¬
velopment. Moyer and Hollander [84, p. 2] attribute the importance of
marketing in that process to the fact that it permits increased agricul¬
tural output to be moved into commercial markets, and since distribution
systems link markets with markets and producers with markets, these
systems equalize and distribute goods from surplus to deficit areas.
Since producers and consumers are separated geographically, production
and consumption cycles are different, food products though harvested

45
intermittently are consumed at fairly regular intervals, and the neces¬
sity of marketing agents is evident to keep goods flowing both geogra¬
phically and through time. The economic development process will suffer
if this distributive function is not well performed.
King [64, pp. 78-9], in analyzing the importance of marketing in
economic development, states that it is desirable that farmers respond
to prices and income incentives for three goals: a nutritional goal,
a price stability goal, and a growth goal. Inefficiencies in the pro¬
duction of marketing services and in the pricing system interfere with
the achievement of such goals. Three basic conditions, according to
Abbott [3, p- 5], are of special importance in assisting market demand
to provide production incentives: reasonably stable prices for agri¬
cultural products at a remunerative level, adequate marketing facili¬
ties, and a satisfactory system of land tenure.
Despite its apparent importance in economic development, late â– 
emphasis on marketing may be due to the centuries-old belief in the
unproductive nature of marketing and middlemen or possibly to the
belief that marketing is an accomodating mechanism and that firms will
appear to provide the necessary services once the need for such services
has been felt. Collins and Holton [16, p. 3&0] have demonstrated the
erroneous nature of the latter point. They emphasize the need for special
attention in transforming the organization and operation of the distri¬
butive sector rather than the physical facilities.
‘ Abbott [1, pp. 87-8] attributes the neglect of marketing in de¬
velopment plans to two possible causes. One is the belief that a
1 aisez faire attitude will better solve prob1ems than if solutions are

included in a plan. The other possibly is the ignorance of planners
about the importance of marketing or their lack of interest in the
subject. Going to the other extreme, there may exist the temptation
of giving marketing an over emphasis and without sufficient attention
to production. Heady and Mayer [^5, p. 31] have already given warnings
about this tendency when they state that both the producing and the
marketing sectors should be considered and tackled together. Two
opposite examples of imbalance are: (l) the case when increased food
production is penalized in the market and the production potential is
not realized because consumer preference places a low value on the
commodity; and (2) the situation when large investments of effort and
funds are made in marketing research and facilities without relating
these investments properly to production conditions.
Times and attitudes about marketing and development are changing
as stated by one author who wri tes..."countering the crude notion of
the non-productivity of marketing is the growing realization that the
activities performed in transforming farm products in space, form, and
time are a useful and necessary part of the economy" [3^, p. 132].
This growing consensus conveys the idea that changes are needed not
only in the distributive sector to help the development process, but
that this sector can actually play a leading role in that process.
Collins and Holton [16, p. 360], in arguing against a passive role
for marketing, state that the distributive sector can under certain
circumstances play a very active role by changing demand and cost
functions in such a way as to encourage the expansion of the agricul¬
tural and manufacturing sectors. Rising productivity, according to

*»7
Fletcher [34, p. 132], creates demand for services produced by different
marketing firms and the strategic position of the distributive sector
gives it a leading role in development. He further argues that in LDCs
there is a need for a relatively heavy emphasis on technological effi¬
ciency as contrasted to economic efficiency (consumer satisfaction is
more important than consumer sovereignty) and that the marketing system
is the necessary connecting link between consumers and an increasing
volume of food and fiber production.
There are many variables influencing the distributive sector in
LDCs. An important publication [67, p. 5] lists the following: the
stage of technology in its agricultural production system and in its
overall economy (the rate of agricultural growth); how well the country's
domestic production can meet the country's food needs (the extent of
the dependence on external food aid) and the extent to which a few
crops make up the bulk of the people's food supply; the extent of ur¬
banization; the level and distribution of income, and the income elas¬
ticities of demand for food; the size of the country, the population
distribution within it, and the rate of population growth; the country's
socio-economic structure and its politico-economic ideology (the environ¬
ment for private investment and the ease of entry into marketing enter-
pr i ses).
Many authors have made important contributions about the role
played by the variables that influence the distributive sector and the
contribution of this sector to the process of economic development [1, 2,
3, 4, 5, 13, 1 ^, 16, 18, 28, 31, 3*», **0, 41, 42, 43, 44, 45, 49, 57, 64,

48
66, 67, 73, 79, 81, 83, 84, 86, 88, 90, 97, 100, 102, 103, 104, 105,
110, 112, 115]. Drucker [28, p. 344] assigns marketing such a criti¬
cal role in the development process as to consider it to be the most
important "multiplier" of such development. Though often neglected,
market system development makes possible full utilization of existing
assets and the productive capacity of an economy, mobilization of
latent economic energy, and development of managerial talent.
Moyer [83, pp. 7-19], however, summarizes well the existing litera¬
ture in several propositions about the role of the marketing system and
marketing institutions. He suggests that they can provide the necessary
means to coordinate production and consumption and provide consumers with
the commodities they need and want. By making available new or improved
products, improved marketing systems can increase the elasticities of
supply and demand. Market systems can also reduce risk by providing
more adequate information flows among participants in the system.
Secondly, markets can incorporate subsistence producers into the ex¬
change economy and also be an important channel for entrepreneurial
talent and capital for other sectors of the economy. Third, as a
result of market extension, market systems may generate pecuniary
and technological economies, both internal and external, for producing
firms. Efficient markets can lower consumer costs by improving dis¬
tribution efficiency, more intensive resource use and less spoilage.
They can also reduce transaction and exchange costs between producers
and consumers.
Most important, and closely related to the problematic situation
in this research, is the fact that marketing can "produce" just as

A9
farming does in the following senses: reducing losses to consumers
is the same as increasing yield; storage augments production for the
off season; providing timely inputs to farmers also increases yield;
improving quality increases val ue (price) though often for marketing
agents beyond the farm level.
Transplanting marketing strategies from the industrialized
countries to the developing countries should be avoided. Currie [18]
has shown that it is ill advised to assume a standard pattern of de¬
velopment for all countries and that trying to apply the marketing
organizations and techniques of the developed countries to LDCs will
not render satisfactory results. This is due to an array of differen¬
ces in marketing efficiency between the two groups of countries ac¬
cording to Chaturvedi [14, pp. 118-23]. While in developed countries
the producer is relatively prosperous, and is linked to and depends
upon, the market, the self-subsistence farmer of LDCs is not. While
in the advanced countries the main source of income of the middlemen
in marketing is their turnover profits, in LDCs the often numerous and
small middlemen generally depend on their margins for their incomes.
Differences in transport and communications, information, storage,
grades, and standards, etc., also prevail between the two types of
countries. For these reasons it is clear that a transplant of tech¬
niques from advanced countries to developing countries will not
necessarily produce satisfactory results. In traditional economies,
on the other hand, marketing firms play a passive role by merely
buying and selling. They can be positive and play a major entre-

50
preneurial role. Development of the banana marketing industry in the
United States started by a ship owner looking for products to haul
back to the U.S. from Jamaica who was later joined by other food mer¬
chants, is a good example.
Marketing and the Theory of Demand in LDCs
A special consideration must be given to the relationship between
marketing and the theory of demand in developing countries. The impor¬
tance of the application of demand theory to developing country problems
is accentuated by the introduction of new technologies coupled with a
complete lack of knowledge about demand conditions for the different
commodities. The excessive variability in the quality and volume of
supply can be a tremendous problem for producers and market organizers
in these countries.
The law of demand states that, ceteris paribus, quantity demanded
of a commodity varies inversely with price. Chaturvedi [lA, pp. 131-2]
has pointed out several reasons why the law of demand can present special
characteristics in LDCs. The law of demand assumes that conditions re¬
garding the means of transport and communications are similar everywhere.
Nevertheless, it sometimes happens that in LDCs, when transport diffi¬
culties occur, price increases are present when demand in a region has
risen even though supplies of the commodity are adequate. Another
characteristic present in LDCs is the fact that, particularly for food-
grains, movements of some commodities follow the directions of the profit

51
trends or the expectations of the middlemen without considering con¬
sumer needs. This may result in surplus in one area while there is a
need for the commodity in another area which lacks the necessary pur¬
chasing power.
Knowledge of demand conditions are of foremost importance for
planning in developing countries. Abbott believes that
...the first stage at which market considerations enter the
planning process is forecasting probable demand as a basis
for fixing production targets. While looking for potential
resources to exploit is one of the first elements in any
plan to accelerate economic growth, decisions on how to
use these resources and at what pace to put their products
on the market must depend on an appraisal of the demand.
This includes both the demands of a growing domestic
population and the demands of international markets in
which a country hopes to sell as a means of earning the
foreign exchange it needs for development...Where less
familiar or more specialized crops enter a plan, care¬
ful attention to consumer tastes, preferences and habits
is essential. Examples of misjudgement on such grounds
are common [1, p. 9*0.
It is necessary, however, that the market demand provide production in¬
centives. Of special importance are, according to Abbott [1, p. 102;
2, p. 3^5], first, reasonably stable prices (without discontinuous
intra or interseasonal changes) at a remunerative level. Farmers will
hesitate before incurring additional work or expense to increase pro¬
duction unless they have confidence that prices will be higher than
costs. Second, adequate marketing channels and facilities must be
provided at the proper time. Farmers will be disappointed if they see
that their increased ouput cannot- be sold due to the lack of a proper
channel. Finally, a satisfactory system of land tenure avoids
large share of the returns from increased output going to the hands of
the landlords.

52
To avoid marketing problems in the future, research on demand
conditions must be conducted. This should include both domestic
and foreign demand. Knowledge of price and income elasticities of
demand can be used to signal producers where, when, and what products
they should produce.
Marketing and the Theory of Supply in LDCs
Of special interest to our concern about traditional and commercial
farms and crops'response to improved technology is the relationship
between marketing and the theory of supply in developing countries.
The law of supply states that, ceteris paribus, quantity supplied of
a commodity varies directly with price.
Developing countries often emphasize increasing production of food
crops by relying on modern yield-increasing technology. Adoption of
the new technology is supposed to foment increased productivity and
production [26].
Technological advance, however, may bring about productivity in¬
creases yet the same level or declines in aggregate production. Due
to major seasonal and cyclic price fluctuations mainly in basic grains
and to small farm income limitations, small farmers in LDCs choose,
quite rationally, to grow only enough of some food crops for home con¬
sumption. Policy makers often desire to secure for the country adequate
increases in the marketed supply of food crops and to determine necessary
2
future changes in land utilization to meet that objective. Knowledge of
2
The impact and implications of foreign surplus disposal in develop¬
ing countries are voluntarily ignored. The interested reader is referred
to some of the relevant literature [33, 62, 63, 91, 109, 111, 121].

53
total and market supply response by traditional and commercial farms
to changes in production, price and income under different regional
conditions has concerned numerous development economists. Major
contributions to an understanding of the forces governing supply
response in "subsistence agriculture" are provided by Wharton [119],
3
Behrman [11], and Krishna [68, pp. 497~547] • The latter has pro¬
vided a comprehensive analysis about agricultural price policy and
economic development, mainly concerned with supply response and price
determination in developing countries.
The behavior of farmers in developing countries relative to a
marketable surplus has been the main focus of several recent more general
studies. Included in this research are the relationships between mar¬
ketable surplus and dual development [23], marketable surplus and eco¬
nomic growth [29], and marketable surplus, dual development, and economic
growth [122]. The relationships between marketable surplus and price
[60, 72, 114], size of landholdings [87] and stages in the process of
development [78] have also gained special attention.
Numerous specific studies related to production and supply of tra¬
ditional and commercial crops, annual as well as perennial, mostly con¬
cerned with estimating the sign and magnitude of the price elasticity of
the marketable surplus, have been conducted [6, 7, 8, 9, 10, 15, 20, 21,
38, 39, 50, 60, 61, 69, 70, 71, 76, 77, 85, 99, 113, 116]- The results
generally suggest that the inverse relationship between surplus and
*3
JThe author does not want to discuss the acceptability of using the
concept of "subsistence agriculture" so broadly. Miracle [82] considers
the use of the term erroneous since agriculture in LDCs, according to
him, is not homogeneous.

price found in some cases can be attributed to two possible causes.
One is tied to the relatively fixed demand for money by traditional
farmers which calls for sales only to the level of money needed. The
second cause is that increasing traditional crop prices may stimulate
an increase in the farmer's income such that the income effect on his
demand for consumption of the crop outweighs the substitution effect
in production and consumption [78]. For either cause, marketable sur¬
plus may be inversely related to price.
A very important recent contribution by Wiens [120] adds risk to
the picture. Wiens, using quadratic programming to examine the impact
of yield uncertainty on peasant allocation of land among crops and
their use of hired factor services, shows that optimization qualified
by risk aversion proves superior to risk neutrality or credit constraints
in explaining peasant allocative behavior.
Despite the growing interest on small farm agriculture [12, 9**,. 82]
the research on supply response in traditional agriculture seems incom¬
plete. A definite explanation of the two causal phenomena producing a
possible negative relationship between surplus and price has not been
provided. Nor has there been an explanation of why the response situa¬
tion happens in some but not all regions of a country, or how one can
predict and measure the effects of that behavior. To complicate the
situation even further, after contemplating their research results on
the subject, Manghas, et_ jaj_. state that price may not be very effec¬
tive in increasing aggregate agricultural output, which implies "a much
less optimistic outlook for the role of price as a development tool, at
present levels of technology, than if price changes induced yield as
well as area changes" [76, p. 685]-

55
The need for a theoretical and analytical framework to enable
economists to analyze the total small farmer basic economic system
is evident. Such a framework would be an important contr i but ion to
the development theory. This research attempts to provide a basis
for more fully understanding supply response criteria inherent to
traditional and commercial agriculture in developing countries.

CHAPTER I I I
THEORETICAL AND METHODOLOGICAL FRAMEWORK FOR INVESTIGATING
TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE
The basic economic system of the Guatemalan small farmer is described
in the first section of this chapter. A second section contains the
method of estimation with the cor responding hypotheses and equations
and the description of how the model has been adapted to the different
regions of the country and the different cropping patterns. The third
section explains the methodology used for computing input acquisition
and product disposition. Finally, data used and implications are briefly
discussed.
Basic Economic System of the Guatemalan Small Farmer
The environment in which a Guatemalan small farmer lives determines
his consumption and selling decisions. A small farmer grows basic grains
mainly for home consumption. At harvest time he disposes of his produc¬
tion in several ways. A large share is kept for family consumption and
other noncash purposes such as feed, seed, payments in kind, etc. If
cash is needed, part of the output may be sold at the time of the har¬
vest. In good years some production may also be saved to be sold through¬
out the year whenever the farmer needs cash or when high prices make
selling worthwhi 1e.
56

57
The hypothetical price-income-consumption (P i C) path developed
in Figure 5 (A) illustrates the small farmer's consumption and selling
decisions and is used to develop his market supply curve for a product.
Due to his subsistence needs, the small farmer's demand and supply
situation for items produced on his farm is somewhat unique. Figure
5 (A) shows a hypothetical pri ce-income-consumption (PIC) path for a
commodity produced and consumed at the farm level. Assume the. farmer
is at point Z, where price is Pg and increases to P^. The farmer's
income will increase. The income effect created by the price increase
will make him move up and along the PIC path. Most food crops pro¬
duced on the farm can be considered as inferior goods; since small
farmers usually have so little income, a small price increase may pro¬
duce a significant change in his income position such that he is willing
to consume less of the product. Since he is his own supplier, he can
cut back on his consumption. If the process is repeated, the hypothe¬
tical price-income-consumption (PIC) path shown in the figure can be
drawn. Total output is fixed at OB and the amount OC is the minimum
necessary for family subsistence and seed for the coming season. If
quantity OB is desired for home consumption and other noncash purposes,
the farmer will not sell any output. However, cash needs or higher
prices throughout the year might induce him to sell some of his pro¬
duct and forego some consumption. For example, if the price is P^, the
farmer keeps OA and sells AB.
The decision process at harvest time and for the short-run, depicted
in Figure 5 (B), is dependent primarily on product price, home consump¬
tion needs, and cash needs to purchase other goods. At harvest total
If the price is P^, the farmer expects to consume OA^
supply is Qj.

58
(A): Firrrr-Long run price-
income-consumption path
(C): Industry--Price-income
consumption path
Figure 5.--Guatema1 an small farmer
(B): Firrrr-Short run home vs.
sales
(D): Industry--Market supply
consumption and selling decisions

59
H M
(Qj - quantity used at home) and to sell A^B^ (Q - quantity marketed).
This decision at harvest time establishes OA^ and as supply and
demand proportions for the year if price stays at P^ . When all of the
output is sold at harvest, no further decisions are possible. If the
farmer did not sell everything at harvest, becomes the new fixed
total supply curve since was sold or consumed. At expected
home use would remain at . However, as price rises to P^, home use
declines to or OA^ and sales are A^B^ thus reestablishing demand
and supply proportions. The process, when induced by increasing
prices, may continue until q"*" reaches the amount where the hypothetical
price-income-consumption path becomes asymptotic to the Y axis at OC,
the minimum needed for family subsistence and seed. It may happen
that, as QT shifts to the left during the marketing period, prices
above P^ result in decreasing quantities marketed. Little or no surplus
available when prices keep rising may bring about indirect relationships
between prices and quantities marketed. For price declines, the process
is also operative and illustrates greater home use relative to sales for
the short run or one season.
From the hypothetical pri ce-income-consumption path for each small
farmer, as illustrated in Figure 5 (A), a community of pr i ce-i ncome-con-
sumption paths can be developed as in Figure 5 (C). The effects of price
and income changes, (e.g., constrained variables) result in movements
along the path. Other variables exert an influence in the position of
the PIC path. While increases in farm size and in the level of education
with other things remaining equal, make the path shift downward, the
opposite occurs as distance to the market and quantity demanded on the
farm increase. If the profitability of other grains goes up, the PIC

60
path also shifts upward. As the PIC path approaches the total production
constraint (Q^) it becomes more elastic. At point Z, the elasticity of
the PIC path is infinite; price is so low at this point that farmers
decide to consume everything they produce since there is no incentive to
forego consumption through sales in the market.
The hypothetical PIC path is used to derive the market supply (Q^)
shown in Figure 5 (D). By starting at point Z and moving up and along
the PIC path, quantities marketed at different prices can be read to
establish' Q^. If the quantities used on the farm (Q^) are added to
the total quantity produced (Q^) is identified.^ At this point, Q* does
not present the completely vertical shape that the fixed total supply
curve shows in sections (A), (B), and (C) of Figure 5- Although is
a fixed amount until the next harvest, it does decrease during the mar¬
keting period as the farmer alters his consumption and selling decisions
due to changes in his income situation produced by price changes. For
H M T
that reason, when Q (0C or MT) i s addecLtoQ. , Q. slopes upward. At P^,
T M
however, both annual supply functions (Q. and Q ) are perfectly inelastic
and will not be affected by further price increases. Here the basic
identity QM H - QH will not be subjected to further alterations until
the following harvest. Since there is an infinite number of hypothetical
Income level and farpj area devoted to the crop in question provide
offsetting influences on Q. which are not measured in this research. As
income rises with an income inelastic demand for a basic grain, consump¬
tion per capita at the. farm level may decline whil^j demand for seed may
expand until the income supply response function Q. becomes perfectly
inelastic. For this reason a fixed Q is assumed.

61
pri ce-income-consumption paths, representing numerous farm families, and
of combinations that can be made between and Q^, and since shifts
M
over the marketing period, there is an infinite number of possible Q
M M
curves as shown by to in Figure 5 (D). Since Figure 5 (D) is
derived from Figure 5 (C), the starting points of all industry supply
functions are completely elastic; such a low price does not induce farmers
to market any output.
M T
Assuming that Q and Q. in Figure 5 (D) are two observable supply
functions, small farm market behavior can be further investigated. At
price Pj, OT is total quantity produced (Q^), AB is the quantity kept at
home (Q^) and OT minus AB is the quantity marketed (Q^). As price goes
J-|
up, Q. will fall until it reaches the minimum amount MT. At P^, for
example, OT is again total quantity produced (0^), CD is the quantity
kept at home (Q ), and OT minus CD is the quantity sold in the market
M M
(Q ). Q. is therefore not a fixed amount but becomes a function of price
throughout the marketing period. Thus, knowledge of those conditions
T M
that induce changes in Q and Q. are necessary to identify both curves
and the implications of their relative locations and shapes.
|_|
Since the levels of Q. observed are not actually purchased in the
market at different prices, we cannot obtain farm family demand func¬
tions, final equilibrium points, and demand elasticities. Interest,
however, is in determining supply responsiveness to changes in farm
size and level of income.
Enterprise combinations utilized by small farmers at different
income levels are closely related to the theory of small farm demand
and supply of basic foods. More specifically, the impact of income
changes on the relative quantities that are produced and marketed from

62
the crop mix as well as land use patterns support the demand and supply
theory. This subsistence, land use and crop mix environment of the
Guatemalan small farmer is characterized by varied levels of risk
aversion as relative incomes change. With few, small and divided plots
of land at his disposal, the small farmer grows primarily traditional
crops although he may also produce some commercial crops where risk is
minimal relative to that of other high value crops. As opposed to low
risk traditional crops grown mainly for subsistence, low risk commercial
crops are a source of income where adversity would not extend beyond
normal weather fluctuations. Low risk commercial crops may also include
crops whose prices are supported by the government. Wheat is a good
example for Guatemala.
The small farmer's behavior within his basic economic system is one
of carefully balanced risk aversion, income maintenance and risk taking.
As depicted in Figure 6, at very low levels of income or farm size the
farmer grows basic grains for subsistence though he may also sell part
of his production. The difference between total quantity produced (Q^)
and quantity marketed (Q.^) of a traditional crop depicts home use re-
quirements for consumption, seed and other purposes (C>t) . Since crop t
is mainly intended for subsistence, the curves show some income respon¬
siveness at very low levels of income and almost none at high income
levels. Because some grains will always be grown due to cultural values,
(corn and beans are good examples), the curves will be similar in shape
and, once the home use requirement is reached, the curves will tend to
become perfectly inelastic (or vertical) regardless of income level.

63
Income
or
Farm S¡ze
Figure 6.--Income-quantity or farm size-quantity relation¬
ships for the Guatemalan small farmer, given his
land constraint

64
As income rises, due to productivity and/or price reasons, the farmer will
divert some of his land into other commercial crops (Q^) while maintaining
his sel f-suff i c iency product ion on less land. In this case, the response
will increase with income up to the point where the farmer has no more
land available for crop production or it is feasible to introduce another
commercial crop.
Thus, as income rises, small farmers with their self-sufficiency
guaranteed, will tend to diversify production by growing high value crops
until the land constraint is reached. Qc in Figure 6 is not produced
until a certain minimum consumption and income level is attained with the
basic and low risk crops. Income responsiveness of the higher value and
higher risk crops is greater than for the traditional crops. At higher
income levels farmers venture into higher risk crops and combine their
production according to income level and land availability. Figure 6
is also operative to determine land use patterns when the vertical axis
is labeled with different levels of farm size.
Method of Estimation
This section presents the methodology used in this study. The
hypotheses to be tested with the corresponding functions and the adapta¬
tion of the model to the different regions and to varied cropping patterns
are also explained.
Hypotheses
Since income-supply relationships are the main focus of this research,
the primary set of hypotheses relates to the respective elasticities. The

65
hypotheses are formulated broadly since it may be the case that a tra¬
ditional crop in one region may be a commercial crop in another region.
The functions, and corresponding elasticities, will behave differently
in each case.
Concerning income elasticities of market supply it is hypothesized
that:
(1) When crops are grown for subsistence, at very low levels
of income, small farmers will market very little. As
income rises small farmers will market more but only up
to a certain amount where they have their self-sufficiency
secured.
(2) If the income of small farmers rises, they will produce
and market successively higher value crops in combination
with subsistence crops and within their land constraint.
Concerning the productivity of basic grains and of competing or
alternative commodities, it is further hypothesized that:
(3) If the productivity of basic grains grown for subsistence
increases due to y i eld-increasing technologies, then small
farmers will produce up to the point where they would have
their self-sufficiency secured with less land.
(4) At low income levels, as alternative crops become more
profitable, small farmers will produce and market wheat
up to a certain amount after which they will shift to
other commercial crops since their income cannot be
increased much more due to the wheat price support limit.

66
Concerning farm size elasticities of market supply, it is hypothe¬
sized that:
(5) When farmers are at the very subsistence level, all avail¬
able land is devoted to traditional crops. As technology
or farm size continues to increase, small farmers will grow
other crops while maintaining their self-sufficiency.
Concerning price elasticities of market supply, it is hypothesized
that:
(6) As the price of basic grains rises, small farmers will
market more output but the percentage increase in supply
will be less than the percentage increase in price.
Concerning production and distribution activities of traditional and
commercial basic grains, it is hypothesized that:
(7) if the productivity of basic grains can increase, and
production gains are obtained at the same time, production
and distribution activities can still be performed adequately.
The Model
Based on the small farm decision process just described, the following
market supply function can be estimated:
<’> a? ' «! - B0 + *| F¡ + b2 e + s3 *i + ^ °¡ + B5 'i + e6
]_
W. + 3, Y. + e.
i 7 i i
2
The Appendix contains a complete specification and discussion of
the mathematical and statistical models.

67
where,
M T
Q. / Q. = percent of grain production that is marketed (kg);
P. = farm price of basic grain i (quetzales/kg), and estimated
in reciprocal form;
E. = education of household head (number of years of formal
education);
A. = total farm size (ha) and estimated in reciprocal form;
D. = distance to the nearest market (km);
I. = quantity of basic grain i demanded at the farm level
for all purposes (kg);
W. = return per hectare in all basic grains except: basic
grain i divided by return per hectare in basic grain i;
and,
Y. = total family income (quetzales/year) and estimated in
reciprocal form.
The reciprocal is chosen for P., Y., and A. because in the theoretical
i i i
presentation the function is hypothesized to slope upward and to become
perfectly vertical at a certain point. Complete inelasticity occurs in
the case of price, when the farmer does not want to sell any part of the
quantity saved for home consumption and seed; in the case of income, when
the subsistence level has been achieved; and in the case of total farm
size, when other crops enter the production system. The rest of the vari¬
ables are estimated in direct form.
M T
The ratio of marketed output to total output (Q. / Q.) is estimated
M T
instead of Q. alone because Q. becomes a different constraint, based on
i i
farm size, for each farmer. The quantity retained for home use varies
considerably among farmers and crops and only a certain maximum percentage
of total supply can be marketed. In a total 1 y commerc i al i zed farm, the

68
ratio equals one, while in a totally traditional farm it equals zero.
A positive sign indicates that the crop becomes more commercial as inde¬
pendent variables increase while a negative sign indicates a tendency to
more traditional, or less commercial crops for the direct variables (E.,
D., I., W.) and the opposite for the reciprocal variables (P., A., Y.).
ill iii
The ratio also becomes smaller or larger at different price levels due
to the total production constraint.
Total farm size (A.) is included instead of area producing each
crop (A.) to account for the differences in farm size and to illustrate
variations in quantities marketed at different levels of farm size.
Therefore, the same observation (A.) per farm is used in the equations
for each basic grain regardless of the amount of land devoted to its
production. The weight (W.) should account for the different basic
grains grown by the farmer and, therefore, any possible substitution
among them. The rest of the variables are self-explanatory.
Price (P.), income (Y.) , and total farm size (A.) will carry nega¬
tive signs if the function behaves as postulated. Quantity demanded at
the farm level (l.) is also expected to carry a negative sign. Distance
to the nearest market (D.) and education (E.) are expected to carry
negative and positive signs, respectively. The relative profitability
ratio (W.) will carry a positive or a negative sign according to the
traditional or commercial nature of the crops in the region.
M T M T
Once Q. / Q. is estimated, both 0. and Q. can be obtained.
ii ii
From the theoretical presentation we know that
(2) q! = Q^ + I .

69
From (l) we can write
(3) <£ = q! . / qT, or
"i
i
i
i
(h) . (Q^ / qT) + I. . (Q¡ / qT)
,M
Solving for Q.,
(5) (1 " Q? / QT) Q^1 = I. . QM / QT
i i
Finally,
(6) Q1? = I . (<£ / qT) / (1 - Q? / q!)
i i
Once (6) is obtained, it can be substituted in (2) and, after adding
I., Q. can also be obtained.
i i
Adaptation of the Model
The model is adapted to specific circumstances in different regions.
M T
For example, when two crops are associated, Q. / Q. for both crops must
be estimated. Price and quantity variables must be converted to weighted
values to permit realistic comparisons and derive realistic conclusions.
In the case of two or more associated crops the following' weight is used:
Let TR. and TQ. be total revenue and total quantity of crop i, respectively,
and TRj and TCJ. total revenue and total quantity of crop j associated with
crop i in one region.
Then,
£TR. / ITQ. = Pw., a weighted price for crop i in the region, and,
ETRj /ETQ. = Pwj> a weighted price for crop j in the region. Then
Q^. / oT. may be estimated as the sume of P . . [Q^ / oT] and
IJ "ij wi i i

70
M T H T
P • • [Q. / Q.J, and Q. . / Q. . will have been given a value figure. In
wj J J U ij
the case of price on the right-hand side of the equation, (P. . qT + P
a!)/ (q¡ + qJ) = P.j, a new enterprise price for an association.
Production and Distribution Activities
Description and quantification of production and distribution acti¬
vities is illustrated in Figure 7- These activities are explained for
every enterprise in the different regions of the country.
The figure contains amount (kgs) and cost (quetzales/kg) of the
different inputs utilized in the production process and the different
ways for disposing of total production. Since figures in each cell take
into account the weight given to each questionnaire, they are intended
to represent good approximations of totals in the region.
Data Used and Implications
Not all farms contained in the sample are used in each of the esti-
M T
mated equations. Q.. / Q. picks up only those farmers selling some of
their output; or in terms of the theoretical presentation, those producing
more than 0C in Figure 5- Furthermore, it seems that the sample failed
to include a considerable number of these farmers, and, since the sample
was intended for a small farm study, only very few of the large farmers
were included. For those reasons, the estimates are conservative. Re¬
sponses will therefore be stronger than shown in the results since both
ends of the spectrum are not considered. In Chapter six, a special
section is devoted to the discussion of the descriptive statistics of
each independent variable, and generalizations and implications of the
resu1ts.

Figure 7.“-Hypothetica1 production and distribution activities for basic grains produced in the
different regions of Guatemala

72
The computations of the production and distribution activites do
encompass all farmers in the sample size. For that reason, averages in
the activities, especially total quantities produced, may not coincide
with those in the estimated equations.
Summary
This chapter has described the theoretical framework which explains
the Guatemalan small farmer's behavior within his basic economic system;
a sytem in which his subsistence needs, the land constraint, and his
income level are the most important variables. The production and dis¬
tribution activities to be described and the equations to be estimated
attempt to quantify that behavior by considering the variables that may
be relevant to his decision making process. The degree of success
achieved in quantifying that behavior is the subject matter of the
following chapters.

CHAPTER IV
PRODUCTION AND DISTRIBUTION ACTIVITIES
Production and distribution activites for each basic grain or
association produced in the different regions of Guatemala are described
and quantified in this chapter. The description by crop, or association,
follows the pattern of analysis utilized in Chapter five. Characteristics
or each crop or association are identified for each region to facilitate
interpretation of the results presented in the remainder of the disser-
tation.
The Input Market
Input use in basic grain production is presented in Table 8. After
briefly defining each production activity, the description focuses on
the relative importance of each activity across enterprises and regions
(Table 9).
Seed Utilization
The activity of seed utilization relates to the total amount of
seed purchased at planting time or stored from a previous harvest.
Some differences in seed management across regions and crops are
present. Of all the associated enterprises, corn-beans in R^ and R^
73

Table 8.--Total inputs used in basic grain production by regions of Guatemala
CROP3
1 nput Activities
C-B
C-B
C-B
C-S
C-B-S
C
C
C
C
C
1
5
6
6
REGION
6
1
3
4
5
6
Seed:
Amount not purchased
*(5,521)
55,952
99,579
36,312
64,017
95,200
68,440
92,460
60,192
49,818
Amount purchased
18,286
5,670
84,582
21 ,720
33,712
1 ,773
3,470
92,460
42,127
25,599
Cos t
5,21)8
2,010
24,753
5,875
9,306
288
755
38,350
13,493
9,672
Modern inputs:
Amount urea
110,676
28,71)9
29,029
30,810
13,750
108,680
98,031
124,921
61 ,427
205,856
Cos t
12,006
3,885
3,641
4,017
1 ,760
13,884
12,885
19,504
8,109
28,560
Amount soil additives
1)70
0
0
0
0
0
238
2,143
0
0
Cos t
28
0
0
0
0
0
28
835
0
0
Amount other chemi cal s280,973
30,61)7
414,700
176,698
157,420
667,818
157,860
594,336
309,582
450,368
Cost
33,300
3,724
47,900
21 ,794
18,760
81,480
19,746
68,973
40,278
58,032
Cost other fertilizers 38
78
809
0
0
720
73
1 ,824
475
22
Cost Pesticides
930
1 ,501
3,124
1 ,740
1 ,218
1 ,551
14,848
39,184
11 ,088
5,220
Labor:
106,808
38,664
193,697
127,981
109,844
247,679
213,988
446,472
206,346
183,638
B
B
B
B
CROP
S
R
R
R
W
W
1nput Activities
1
4
5
6
REGION
4
4
5
6
1
6
Seed:
Amount not purchased
13,021)
3,773
12,040
85,842
11,448
32,328
9,681
57,760
263,676
5,210

Table 8.--continued
CROP
1nput Act ivities
B
B
B
B
S
R
R
R
W
w
1
**
5
6
REGION
it
b
5
6
1
6
Seed:
Amount purchased
2,256
19,728
7,520
39,80*1
13,692
3**, 896
3**,20**
**3,605
311,922
51 ,0**8
Cost
805
7,200
1 ,755
13,**23
3,**16
8,027
8,262
11 ,088
50,998
9,552
Modern inputs:
Amount urea
b,bb3
0
89**
16,780
355
37,296
21 ,7**0
bb,**60
251 ,187
8,562
Cost
636
0
]bb
2,136
55
5,992
3,290
5,265
31,209
3bb
Amount soil additives
0
0
0
0
0
0
0
0
7,15**
0
Cost
0
0
0
0
0
0
0
0
7**7
0
Amount other chemicals
5b,333
7,856
13,508
237,363
29,310
63,**68
13,572
196,9 **0
1,30**,256
117, **61
Cost
6,325
928
2,068
31 ,150
3,200
7,82**
1 ,690
23,120
137,280
1*4,760
Cost other fertilizers
; 6
0
b2
'**5
55
32b
80
**25
565
0
Cost pesticides
630
57b
1,**56
1 ,995
2 ,** 16
15,221
1, bbb
5,222
11,970
910
Labor:
16,872
21,080
25,9****
109,020
108,66*4
65,760
55,977
83,810
2b7,0bb
26,125
aC,B,S,R, and W
represent
corn, beans,
sorghum,
rice, and
wheat, respectively.
Amounts
are given
in kgs.,
except
labor which is given
in man days; costs are
given in
quetzales,

Table 9.—Relative importance of inputs used in basic grain production by regions of Guatemala
C-B
C-B
C-B
C-S
C-B-S
C
C
C
C
C
B
B
B
B
S
R
R
R
W
W
1nput Activities
1
5
6
6
6
1
3
4
REGION
5 6
1
4
5
6
4
4
5
6
1
6
Seed purchased:
Average use per hectare 12
14
26
13
19
27
11
17
20
18
67
67
56
53
14
46
66
104
148
131
Average cost per hectare 3
4
8
4
5
4
3
7
6
7
25
24
15
17
4
9
15
17
22
25
Percent of total seed used- 28
9
46
37
35
2
5
50
41
34
15
84
38
32
55
52
78
43
54
91
Seed not purchased:
Average use per hectare 22
36
27
10
19
38
16
21
26
22
52
47
58
61
11
51
51
78
163
154
Percent of total seed used 72
91
54
63
65
98
95
50
59
66
85
f6
62
68
45
48
22
57
46
9
Urea:
Average use per hectare
77
58
41
36
25
127
179
74
79
128
270
0
32
169
16
170
105
129
116
195
Average cost per heactare
9
8
4
5
• 2
16
23
11
11
17
43
0
5
23
3
26
15
16
14
22
Soi1 add i ti ves:
Average use per hectare
32
0
0
0
0
0
3
65
0
0
0
0
0
0
0
0
0
0
172
0
Average cost per hectare
2
0
0
0
0
0
3
6
0
0
0
0
0
0
0
0
0
0
12
0
Other chemicals:
Average cost per hectare
15
7
10
9
7
36
15
18
25
23
37
17
21
21
19
26
11
25
40
41

Table 9."'continued
Input Activities
CROP3
C-B C-B C-B C-S C-B-S CCCCCBBBBSRRRWW
REGION
1 5 6 6 6 134561456445616
Other ferti1izers:
Average cost per hectare
Pesticides:
Average cost per hectare
Labor:
Average use per hectare
1 1.7 0
4 3 2 1
45 43 42 54
0 11 22 16 410352 11 1230
1 44686 12 61375154647
37 101 100 56 57 62 92 66 79 74 60 59 92 85 88 66
-vj
3C, B, S, R, and W represent corn, beans, sorghum, rice, and wheat, respectively. Amounts (average use) are
given in kgs., except labor which is given in man days per hectare, average costs are given in quetza 1 es/kg,/ha.

78
is the heaviest user of seed per hectare. Corn-beans in R^ and R^_ is
most dependent upon stored seed.
Land scarcity in Rj calls forth more intensive production of
corn and beans as single crops, evidenced by the highest application
of seed per unit of land. This region also depends more on stored
corn and bean seed than the remaining regions.
In rice production, average seed use per hectare is higher in R^
than in R^ and R^ while depends more on purchased seed. The main
difference found in wheat production is an almost complete dependence
on seed purchased in R^, as opposed to an even distribution in R^ , the
latter being a more subsistence region that the former. Also, less
wheat seed is used per hectare when it is purchased than when it has
been stored.
In generai, seed becomes linked to product sales, seed storage,
and seed purchase decisions. Thus, variation does prevail in the per¬
centage of total production retained to be used as animal feed and
seed and that percentage of seed which is purchased (Table 10).
Urea Applicat ion
Average amounts and cost of urea per hectare suggest that usage
of this input is fairly common. Although urea application appears
for all crops, except for beans in R^, some of the crops contain
only a small number of observations; these crops are wheat in R^,
corn in R^, beans and rice in all three regions, sorghum in R^, and
corn-beans-sorghum in R^. For the remaining crops, no major differences
in either average use or average cost of urea per hectare are found.

79
Table 10.--Seed purchase and sale proportions relative to total production
and total seed use
CROP
REGION
4
b c
--Percent-
b c
C-B
4.8
28.0
—
—
—
5.0
9.0
5.6
46.0
c-s
—
— —
—
—
—
—
— 13.4
37.0
C-B-S
—
— —
—
—
—
—
— 12.8
35.0
C
6.6
2.0 3.5
5.0
1.8
50.0
4.4
41.0 5.4
34.0
B
9-8
15.0
—
5.0
84.0
5.4
38.0
5.8
32.0
S
—
— —
1.6
55.0
—
—
— —
—
R
—
— —
—
2.2
52.0
1.8
78.0 5.3
43.0
W
8.7
54.0
—
—
—
—
— 0.9
91 .0
C, B, S, R, and W represent corn, beans, sorghum, rice, and wheat,
respectively.
^Feed and seed retained as a percent of total production.
Q
Seed purchased as a percent of total seed used.

80
Use levels do differ between associated crops and single crops where
rates per hectare average 47.4 kgs and 119-3 kgs., respectively.
Soi1 Add iti ves
This activity, with use limited to only four crops, contains
amounts of calcium oxide and other soil correctives applied. The
appearance of only three or less observations in every case signals
the extremely limited use of this chemical input in basic grain pro¬
duct ion.
Other Chemicals
Application of chemical fertilizers other than urea is heavier
than that for any single input as evidenced by the use of chemicals
in all enterprises. Average costs per hectare are the highest in
wheat production in both Rj and R^, and the lowest in all associa¬
tions and in rice in R^. The remaining crops utilize similar amounts
per hectare. Again associated crops utilize only Q9.6 worth of chemi¬
cal fertilizers per hectare compared with Q25 for single crop enter-
prises.
Other Ferti 1izers
This activity encompasses the utilization of other fertilizers,
sprays, etc., which are recorded as an average cost per hectare. Very
limited observations of use for each enterprise confirms the minor
role of other fertilizers in basic grain production.

81
Pes ti cides
Under this activity, average cost per hectare of applying insec¬
ticides, herbicides, and other chemicals utilized in pest control are
recorded. Although used on every enterprise, pesticide application
is not very generalized among farmers. Average cost per hectare for
pesticide use varies substantially but is particularly high at Q12 or
more for rice in R^ and beans in R^ and R^. Most enterprises and
regions display pesticide costs at less than Q5 per hectare. Pesti¬
cide costs per hectare for single crops average Q7.1 compared to Q2.2
for associations.
Labor
Labor utilization encompasses all phases of agricultural activi¬
ties, from soil preparation to harvesting and marketing the final-
product. Since it contemplates cash payments as well as family labor,
the word jornal used in the questionnaire is assumed to mean man day.
Except for the associations, where employment per hectare is very
similar, all enterprises show different levels of employment by region.
In corn production, Rj and R^ employ more workers per hectare than
R^, Rj_, and R^. For beans, R^ is the largest employer, while R^ and R^
use more labor per unit of land than R^ in rice production. Wheat
production requires more labor in R^ than in R^.
For all of the crops present, Rj is the largest employer. Perhaps
this is a result of the subsistence nature of the region. In general,
however, associated crops utilize substantially less labor (**4.2 man
days per hectare) than do single crops (75-8).

82
The Product Market
Distribution of total basic grain production is presented in
Table 11. Emphasis is given to the relative importance of the dis¬
tribution activities and the major differences encountered across
crops and regions (Table 12). A brief definition of each activity
is also presented at the beginning of each sub-section.
Total Production
Average production per hectare, differing among enterprises, is
very similar for each particular crop grown in different regions.
Yield differences, of course, are correlated with the nature of the
crop.
For the associations average production per unit of land is very
similar across regions. However, when the same crops are grown alone,
corn and sorghum exceed the association yield levels while bean yields
fall below those of the associations.
Rice production shows no major differences in average production
per hectare across regions. In wheat yields are somewhat hjgher in R^
than in R^ probably resulting from heavier chemical input usage.
Animal Feed and Seed
This item pertains to that part of total production set aside by
the farmer to be used as seed in the future or as animal feed. The
activity is a fairly generalized practice as evidenced by a large
number of observations obtained in each crop, with the exception of
6'
wheat in R

Table 11.--Distribution of total basic grain production by regions of Guatemala
CROP3
Distribution
C-8
C-B
C-B
C-S
C-B-S
C
C
C
C
C
1
5
. 6
6
REGION
6
1
3
4
5
6
Total Production
2,776,974
1,366,778
5,332,982
4,682,233
3,701 ,922
5,176,481
8,432,820
20,590,494
6,830,277
7,309,947
Feed, Seed
134,400
68,794
297,183
629,004
473,904
341,850
298,870
363.392
300,362
397,761
(4.8)
(5.0)
(5.6)
(13:4)
(12.8)
(6.6)
(3-5)
(1.8)
(4.4)
(5.4)
Family Consumption
898,562
238,606
1,425,747
1,046,061
723,168
2,550,702
900,144
2,422,728
1,382,814
1 ,838,688
(32.4)
(17.5)
(26.7)
(22.3)
(19.5)
(49-3)
(10.7)
(11.8)
(20.2)
(25.0)
Processing
0
0
0
0
0
0
0
0
0
14,284
• (0.2)
Rent Payments
20,089
(0.7)
0
49.845
(1.0)
33,930
(0.7)
35,770
(1.0)
6,528
(0.1)
14,141
(0.2)
0
32,168
(0.5)
537,040
(7.6)
Sales "in kind"
0
2,922
(0.2)
99,300
(1.9)
105,710
(2.3)
99,300
(2.7)
26,296
(0.5)
115,182
(1.4)
3,578
(0.02)
16,920
(0.25)
90,228
(1 .2)
Donat ions
16,192
27.090
11,970
1 ,500
1 ,820
12,470
4,240
18,984
55,330
4,820
(0.6)
(2.0)
(0.2)
(0.03)
(0.05)
(0.2)
(0.05)
(0.09)
(0.8)
(0.07)
Stolen, Damaged, Lost
37,750
(1.4)
73,984
(5.3)
15,656
(0.3)
14,920
(0.3)
0
50,193
(1.0)'
29,705
(0.35)
97,860
(0.5)
27,183
(0.4)
45,432
(0.6)
Total Sold for Cash
1,669,981
955,202
3,433,281
2,851,108
(60.97)
2,367,960
2,188,442
7,070,538
17,638,952
5,015,500
4,361 ,694
(60.1)
(70.0)
(64.3)
(63.95)
(42.3)
(83.8)
(85.79)
(73.4)
(59.93)
1ndeca
0
0
0
b
0
0
0
0
b
0
M idd 1eman
b
b
b
b
2,367,960
b
b
b
b
b
Consumer
b
b
b
0 •
0
b
b
b
b
b
Total Expend, in Mkting.
8,352
9,063
13,344
9,560
8,616
11,025
8,555
54,285
19,488
12,192

Table 11.--continued
CROP3
Oi stribution
B
B
B
B
S
R
R
R
W
W
Activities
1
4
5
6
REGION
4
4
5
6
1
6
Total Production
173,800
271,040
320,809
1,788,263
2,751 ,904
2,379,488
1,380,544 2,496,655
4,967,966
448,722
Feed, Seed
16,962
13,596
17,024
103,008
44,760
52,948
25,083
132,768
430,650
3,927
(9.8)
(5.0)
(5.3)
(5.8)
(1.6)
(2.2)
(1.8)
(5.3)
(8.7)
(0.9)
Family Consumption
64,085
54,211
35,608
323,963
73,552
18,468
11,737
53,225
215,016
0 03
(37.0)
(20.0)
(17.3)
(18.0)
(2.7)
(0.8)
(0.85)
(2.1)
(4.3)
Processing
0
0
375
(0.12)
0
0
0
0
0
942
(0.02)
0
Rent Payments
0
717
(0.3)
0
58,208
(3-3)
0
0
0
89,246
(3.6)
0
0
Sales "in kind"
0
0
0
0
0
0
0
0
4,026
(0.08)
0
Donations
274
(0.16)
0
0
548
(0.03)
0
0
0
0
13,140
(0.27)
0
Stolen, Damaged, Lost
940
(0.54)
1,135
(0.4)
122
(0.04)
4,380
(0.25)
5,358
(0.2)
0
1,824
(0.13)
2,948
(0.1)
101 ,384
(2.0)
1,070
(0.2)
Total Sold for Cash
91,539
201,381
247,680
1,298,156
2,628,234
2,308,072
1,341,900
2,218,468
4,202,808
443,725
(52.5)
(74.3)
(77-24)
(72.62)
(95-5)
(97.0)
(97.22)
(88.9)
(84.63)
(98.9)
1ndeca
0
0
0
b
0
0
b
0
b
b
Middleman
b
b
b
b
2,628,234
2,308,072
b
2,218,468
b
b
Consumer
b
b
b .
b
0
0 :
b
0
b
b
Total Expend, in Mkting.
900
780
884
4,725
12,581
3,690
5,320
3,510
26,690
4,209
aC, B, S, R, and W represent corn, beans, sorghum, rice, and wheat, respectively. Amounts are given In kgs; marketing expenditures
are given in quetzales. Figures in parentheses are percents of production going to that activitity.
^Impossible to determine due to the coding procedure used.

Table 12.—Relative importance of the distribution of total basic grain production by regions of Guatemala
CROP3
Distribut ion
C-B
C-B
C-B
C-S
C-B-S
C
C
C
c
r*
w
1
5
6
6
REGION
6
1
3
1*
5
6
Production
(average kgs. per ha.)
105**
999
1007
111*3
1000
1636
1737
1889
1575
1676
Product Disposition:
Feed, seed
(average kgs. per ha.)
él*
50
76
183
13**
121*
11*3
89
113
132
Family consumption
(average kgs per family)
1520
790
1269
1529
1370
1090
1579
11*85
1156
1161*
Processing
(average kgs, per ha.)
0
0
0
0
0
0
0
0
0
1296
Rent payments
(average kgs. per ha.)
592
0
232
221
172
927
208
0
872
1160
Sales "in kind"
(average kgs. per ha.)
0
58
308
352
208
367
268
163
196
606
Donat ions
(average kgs. per ha.)
31*
61*
80
14
7
168
25
61
533
76
Stolen, Damaged, Lost
(average kgs. per ha.)
31*
50
56
80
0
195
69
11*8
11*2
157
Cash sales
(average kgs. per ha.)
685
791
639
697
637
1057
11*25
1555
1297
1158
Marketing Expenditures:
Average per kg.
.005
.01
.001*
.003
.001*
.005
.001
.003
.001*
.003
Percent of price received
by farmers in the region
3.9
7.1
2.2
2.8
2.7
8.3
1.2
2.8
3.9
2.7

Table 12.--continued
Distribution
B
B
B
B
CROP
S
R
R
R
W
W
1
4
5
6
REGION
4
4
5
6
1
6
Production
(average kgs. per ha.)
732
757
862
907
1380
1848
2040
1959
1442
1181
Product Disposition:
Feed, seed
(average kgs. per ha.)
79
59
70
75
116
80
80
132
174
179
Family consumption
(average kgs. per ha.)
224
310
191
267
575
131
267
134
346
0
Processing
(average kgs. per ha.)
0
0
161
0
0
0
0
0
62
0
Rent Payments
(average kgs. per ha.)
0
65
0
472
0
0
0
1622
0
0
Sales "in kind"
(overage kgs. per ha.)
0
0
0
0
0
0
0
0
78
0
Donations
(overage kgs. per ha.)
129
0
0
29
0
0
0
0
92
0
Stolen, Damaged, Lost
(average kgs. per ha.)
202
81
43
44
70
0
648
90
150
108
Cash Sales
(average kgs. per ha.)
576
658
767
675
1451
1781
1966
1741
1205
1169
Marketing Expenditures:
Average per kg.
.01
.004
.004
.004
.005
.002
.004
.002
.006
.01
Percent of price received
by farmers in the region
3.7
1.2
1.7
1.5
4.6
1 .2
4.2
10.2
3-7
6.1
3C, B, S, R, and W represent corn, beans, sorghum, rice, and wheat, respectively.

87
The average amount of rice production per hectare saved for seed
and animal feed purposes shows some regional variation among enterprises.
The corn-sorghum and corn-beans-sorghum associations of save more
than twice the amount saved from corn-beans of R , R , and R¿. In
1 5 o
corn production, R^ saves the least for seed and feed purposes, while
all regions keep a similar amount for bean production. Concerning
rice, R, and R_ save an identical amount, while that stored in R- is
’45 6
somewhat higher.
Family Consumption
The amount set aside at harvest time for the sole purpose of
family consumption is contained in this activity. Average family
consumption of basic grains, with the exceptions of wheat and rice,
is relatively large and does not show major regional differences.
Average family consumption along with total production is lower
in the corn-beans enterprise of R,. than in the rest of the associations,
In corn production, R^ and R^ show a somewhat higher consumption than
R., R", and R¿, while in beans, R, and R_ save less for future home
l 5 o 15
consumption than R^ and R^.
Rice consumption is higher in R<_ and lower and nearly equal in R^
and R^. Wheat is not consumed in R^ and very few observations appear
in R, .
Processing
Throughout Guatemala a very minor amount of basic grains is set
aside at the farm level for processing. Only one observation, each

88
in corn of R^ and in beans of Rj_, and two observations in wheat of
Rj, appeared in the sample.
Rent Payments
The product distribution activity of rent payments includes not
only payments made for the use of the land but also payments for equip¬
ment and house rentals. Although this practice is found throughout
the country, the small number of observations in the sample leads one
to believe that it is not a very common practice. Corn is, by far,
the most important crop in this activity.
Sales "in Kind"
That part of production exchanged for goods and services other than
cash or rent payments is included in this activity. Corn is again the
crop most commonly used for this purpose. The small number of obser¬
vations per crop again suggests that this is not a very generalized prac¬
tice.
Donations
Included in donations is the amount of total production given to
relatives and friends for which no renumeration was received. This
practice is more common than rent payments and sales "in kind". Corn
again is the crop most used for donations.
Total Losses
Production damaged, lost, or stolen after harvest appears in all
crops with the exception of rice in R^ and corn-beans-sorghum in R^.

89
However, failure of interviewers to consistently record losses makes
it difficult to assess the relative variation of losses among crops
and by regions within crops.
Cash Sales
Sales for cash cover all production disposed of in exchange for
currency. Variations depend on farm demand for production and consump¬
tion purposes.
Average sales per hectare, among the associations are higher in
the corn-beans enterprise of than in the remaining associations.
Being the basic subsistence cropping pattern, with high levels of home
demand, associations present lower average sales than the rest of the
crops. Corn sales are similar in all regions except for R^ where they
are somewhat lower. Average cash sales of beans per hectare do not
present sharp variations, excluding a lower amount in Rj.
Rice sales are very close in R^ and R^ but somewhat higher in R^.
Average cash sales of wheat per hectare do not vary substantially be¬
tween Rj and R^.
Marketing Expenditures
Expenses incurred by the farmer in marketing his products include
the cost of containers (boxes, bags, etc.) and the cost of transporting
the product, either by truck or animal, from his farm to the market.
Although marketing expenditures per kilogram of product sold are
generally one cent or less, differences are observed when these ex¬
penditures are expressed as a percentage of the average price received

90
by the farmers in the region. Enterprise variation in marketing costs
from greatest to least are wheat, r ice, sorghum, corn, followed by the
associations and, finally, beans. R^ tends to experience the highest
marketing costs followed by and R^, whi 1e R^ displays the greatest
amount of variation ranging from 1.5 percent for beans to 10.2 percent
for rice (Table 13).
Summary
Production and distribution activities of basic grains reveal major
differences among crops and regions. Some of these findings are used in
the analyses and implications in the chapters to follow.
Production of basic grains from the input standpoint is most in¬
fluenced by seed and fertilizer costs. While fertilizer tends to be
universally utilized, but at different levels depending upon crops
and regions, soil additives and pesticides are used to a minor degree.
Seed becomes closely linked to product sales, seed storage, and seed
purchase decisions.
Corn, rice, and wheat are the crops employing more workers per
hectare, followed by beans and the associations. Except for the
associations, where employment per unit of land is very similar, all
enterprises show different levels of employment by region.
Total production also presents differences among crops relative
to yields and product distribution. Average production per hectare
is very similar for each crop grown in different regions. However,
when the crops of the associations are grown alone, yield rises above
the average for the associations for corn and sorghum while bean yields
are below those of the associations.

91
Table 13•““Marketing expenditures as a
by enterprises and regions
percent of
average price
received
CROP3
1 3
REGION
1*
5
6
C-B
C-S
C-B-S
C
B
S
R
W
3.9
8.3
3.7
3.7
1.2
-Percent-
2.8
1 .2
A.6
1 .2
7-1
3.9
1.7
A. 2
2.2
2.8
2.7
2.7
1.5
10.2
6.1
aC, B, S,
respect ively.
R, and W, represent corn, beans, sorghum, rice, and wheat,

92
Average family consumption, excluding wheat and rice, is relatively
large and does not show major regional differences. Production set aside
for processing, sales "in kind", and donations are rarely present with
corn being the most important crop used for these activities.
Variations found in cash distribution category depend on farm
demand for production and consumption purposes. For example, being
the basic subsistence enterprises, the associations present high levels
of home demand and, therefore, lower average sales than the rest of
the crops. Expenditures per kilogram of product marketed are generally
one cent or less but, when expressed as a percentage of the average
regional price, from highest to lowest, the ranking is wheat, rice,
sorghum, corn, the associations, and beans.

CHAPTER V
TRADITIONAL AND COMMERCIAL FARM SUPPLY RESPONSE
To explain and analyze the results obtained from the empirical
model is the objective of this chapter. Regression coefficients are
interpreted, the computed elasticities are explained, and income,
farm size, and price-quantity relationships are discussed for each
basic grain or association grown in each region of Guatemala. A
summary of the results at the end of the chapter serves an an intro¬
duction for the discussion of theimpllcatións in the following
chapter.
Associations
The corn-beans association is found in R,, Rr, and R¿, while the
I 5 b
corn-sorghum and the corn-beans-sorghum associations are only present
in R^. The regression coefficients obtained for each of these associa
tions (Table 14 and Table 15), the income, farm size, and price elasti
cities (Table 16 to Table 18), and the income, farm size, and price-
quantity relationships (Figure 8 to Figure 10) strongly support the
conceptual model by illustrating the typical behavior of traditional
enterprises.
93

Table 14.--Regress ion coefficients for each basic grain or association by regions of Guatemala
a
Region
Crop
Constant
P.
1
E.
i
A.
1
0.
1
1 .
1
w.
1
Y.
d.f.
R2
1
C-B
0.27392
-0.00524f
(0.00419)
0.00482f
(0.00541)
-0.08943k
(0.01974)
0.00024
(0.00040)
-0.00001b
(0)
0.00!44d
(0.00099)
-10.61613k
(4.25824)
55
.33
5
C-B
0.28718
-0.004159
(0.00500)
0.00364
(0.01175)
-0.05829f
(0.05218)
0.00126d
(0.00093)
-0.00001r
(0.00001)
0
(0)
-6.04527
(9-61876)
26
.02
6
C-B
0.34978
-0.00388
(0.00642)
0.00647d
(0.00481)
-O.C3l92d
(0.05403)
-0.00049
(0.00082)
-0.00003k
(0.00001)
-0.00412
(0.00753)
-16.55984k
(7.64936)
37
.44
6
c-s
0.19378
-0.00112
(0.00267)
0.00540s
(0.00665)
-0.05217f
(0.05855)
-0.00074f
(0.00076)
-o.ooooib
(0)
0.01147k
(0.00428)
- 7 - 57932 ^
(7.34657)
30
.3^
6
C-B-S
0.51144
-0.0I0839
(0.01299)
0.00509
(0.01283)
-0.36586°
(0.14030)
-0.00335f
(0.00326)
-0.00002°
(0.00001)
-0.02748
(0.05376)
20.90172d
(14.82739)
8
.50
1
C
0.44802
0.0288413
(0.01312)
0.01116
(0.01686)
-0.14456°
(0.07254)
0.00176d
(0.00113)
-0.0001ib
(0.00003)
0.00129f
(0.00148)
-20.4l058b
(7.41719)
78
.28
3
C
1.03937
-0.00049
(0.00162)
0.00699
(0.01321)
-0.37019k
(0.13443)
0.00019
(0.00092)
-0.00006b
(0.00001)
-0.05028b
(0.01877)
-105.81248b
(16.74541)
43
.70
'4
C
1.01516
-O.OOI93
(0.00502)
-O.OO305
(0.01266)
-0.20645k
(0.07638)
0.00035
(0.00063)
-0.00007k
(0.00001)
0.01868b
(0.00524)
- 75.78100b
(8.82157)
200
.44
5
C
0.76560
0.00881b
(0.00380)
0.01286b
(0.00528)
-0.08178°
(0.04451)
-0.00129d
(0.00099)
-0.00008b
(0.00001)
-O.OOO29
(0.00126)
- 39-90728b
(4.50239)
242
.38
6
C
0.46929
0.02270b
(0.00897)
0.01256f
(0.01301)
-0.00962
(0.7740)
-O.OOO52
(0.00171)
-0.00001f
(0.00001)
0.00352°
(0.00178)
- 32.85251b
(9.^0590)
133
.12
1
B
0.33231
0.07544k
(0.02915)
-0.020719
(0.02981)
0.31937k
(0.11896)
0.00010
(0.00139)
-0.00004
(0.00006)
-O.OOO7I
(0.00367)
- 16.94399b
(5-60921)
13
.48
5
B
0.76875
0.005329
(0.00665)
0.00880
(0.02105)
-0.02692°
(0.01234)
-0.001889
(0.00261)
-0.00013^
(0.00012)
0.00014
(0.00151)
- 11.58908d
(8.50285)
55
.01

Table 14 .--continued
Region
Crop
Constant
P.
1
E.
i
A.
i
d. ;
i
1 . w.
1 1
Y.
i
d.f.
R2
6
B
0.63009
0.03663b
(0.01099)
0.01075f
(0.011^9)
0.09483d
(0.06430)
0.00046
(0.00082)
-0.00020b
(0.00003)
-0.00067b
(0.00026)
-32.08327b
(7.48973)
116
.34
4
S
1.04221
0.00095
(0.00953)
-0.01663f
(0.01608)
0.03633
(0.06260)
0.00087f
(0.00069)
-0.00015b
(0.00004)
0.00807b
(0.00320)
-27.O6I31d
(16.50459)
34
.40
4
R
0.9^006
0.00730b
(0.00238)
0.00957°
(0.00542)
0.01260
(0.02230)
-0.00049°
(0.000271
-0.000l2b
(0.00003)
0.00669b
(0.00147)
- 7.14182d
(5.18718)
44
.45
5
R
0.98878
0.000639
(0.00090)
0.00077
(0.00227)
-0.12 3o6d
(0.07980)
0.00017
(0.00037)
-0.00004b
(0.00001)
-0.00032
(0.00218)
-10.63218b
(4.37460)
42
.23
6
R
0.88339
-O.OO58I
(0.01153)
0.01630f
(0.01713)
-0.02060
(0.19699)
0.005209
(O.OO678)
-0.00004b
(0.00001)
0.00172s
(0.00223)
-76.41856°
(31.31350)
20
UT
1
W
0.92030
-0.00893f
(0.00871)
0.01989b
(0.00509)
-0.03073C
(0.01631)
0.00019
(0.00049)
-0.00020b
(0.00002)
0.01076°
(0.00648)
- 3.37986b
(0.96901)
196
.37
6
W
1.02771
-O.OO33Id
(0.00225)
-0.00206f
(0.00188)
-0.02066f
(0.01798)
-0.00012
(0.00028)
-0.00031b
(0.00001)
-0.01455°
(0.00580)
0.01958
(0.92662)
17
.96
ar.
Figures
in parentheses
are standard
errors. C,
B, S, R, and
W represent
corn, beans,
sorghum,
rice, and wheat,
respect ively.
^Significant at the 99 percent level.
CSignlficant at the 95 percent level.
^Significant at the 90 percent level.
Significant at the 80 percent level.
Significant at the 60 percent level.
Significant at the 50 percent level.

96
Table 15.“"Sign and significance level of the regression coefficients
for each basic grain or association by regions of Guatemala
Region
Crop3
P;
E.
i
A.
i
D.
i
1 .
i
W.
i
Y.
i
1
C-
B
-.60
+. 60
-.99
+ .00
-.99
+ .90
-.99
5
c-
B
-.50
+ .00
-. 60
+ .90
-.60
+ .00
-.00
6
c-
B
-.00
+ .90
-.90
+ .00
-.99
-.00
-.99
6
c-
S
-.00
+ .50
-.60
-.60
-.99
-.99
-.60
6
c-
B-S
-.50
+ .00
-.95
-.60
-.95
-.00
+ .90
1
c
+ .99
+ .00
-.95
+ .90
--99
+ .6o
-.99
3
c
-.00
+ .00
-.99
+ .00
-.99
-.99
-.99
A
c
-.00
-.00
-.99
+ .00
-.99
+ .99
-.99
5
c
+ .99
+ .99
-.95
-.90
-.99
-.00
-.99
6
c
+ .99
+. 60
-.00
-.00
-.60
+ •95
-.99
1
B
+ .99
-.50
+ .99
+ .00
-.00
-.00
-.99
5
B
+ .50
+ .00
-.95
-.50
-.60
+ .00
-.90
6
B
+ .99
+ .60
+ .90
+ .00
-.99
-.99
-.99
a
S
+ .00
-.60
+ .00
+ .60
-.99
+ .99
-.90
a
R
+ .99
+ .95
+ .00
-.95
-.99
+ .99
-.90
5
R
+ .50
+ .00
-.90
+ .00
-.99
-.00
-.99
6
R
-.00
+ .60
-.00
+ .50
-.99
+ .50
-.95
1
W
-.60
+ .99
-.95
+ .00
-.99
+ .95
-.99
6
W
-.90
-.60
-.60
-.00
-.99
-.95
+ .00
ac,
B,
s,
R, and W
represent
corn,
beans, sorghum, rice,
and wheat,
respect ively.

Table 16.--Income elasticities of market supply for each basic grain or association by regions of Guatemala
CROP3
. b
Income
C-B
C-B
C-B
C-S
C-B-S
C
C
C
C
C
REGION
Í
5
6
6
6
1
3
4
5
6
50
12.56720
5.89896
22.43350
16.71250
16.71130
6.08591
49.41400
34.97740
12.03280
10.25430
100
3.14)80
1.47468
5.60310
4.17796
4.17770
1.52148
12.35350
8.74437
3.00820
2.56353
150
1.39636
0.65525
2.49230
1.85663
1.85669
0.67621
5.49045
3.88633
1.33694
1.13536
200
0.78545
0.36861
1.40209
1.04453
1.04446
0.38037
3.08837
2.18609
0.75205
0.64089
LO
400
0.19636
0.09)97
0.35052
0.26)13
0.261)2
0.09509
0.77209
0-. 54652
0.18801
0.16022
600
0.08727
0.04074
0.15579
0.11606
0.1)605
0.04226
0.34315
0.24290
0.08356
0.07)21
800
0.04909
0.02293
O.O8763
0.06528
0.06528
0.02377
0.19302
0.13663
0.04700
0.04006
1000
0.03142
0.01464
0.05608
0.04178
0.04178
0.01522
0.12354
0.08744
0.03008
0.02564
1200
0.02182
0.01000
0.03895
0.02902
0.02901
0.01057
0.08579
0.06073
0.02089
0.01780
1400
0.01603
0.00732
0.02861
0.02132
0.02132
0.00776
0.06303
0.04461
0.01535
0.01308
1600
0.01227
0.00561
0.02191
0.0)632
0.01632
0.00594
0.04826
0.03416
0.01175
0.01001
1800
0.00970
0.00439
0.01731
0.01290
0.01290
0.00470
0.03813
0.02699
0.00929
0.0079)
2000
0.00786
0.00366
0.0)402
0.0)045
0.01045
0.00380
0.03088
0.02186
0.00752
0.00641
2200
0.00649
0.00293
0.01159
O.OO863
O.OO863
0.00314
0.02552
0.01807
0.00622
0.C0530
2400
0.00546
0.00244
0.00974
0.00725
0.00725
0.00264
0.02145
0.015)8
0.00522
0.00445
CROP3
r, b
1ncome
B
B
B
S
R
R
R
W
W
REGION
1
5
6
4
4
5
6
1
6
50
2.88532
2.866)6
9.69734
12.96830
3.31305
2.95055
44.35290
0.11281
0.00360
100
0.72)33
0.71654
2.42432
3.24206
0.82826
0.68178
11.08822
0.02820
0.00087
150
0.32055
0.31842
1.07746
1.44084
0.36809
0.30300
4.92803
0.01253
0.00037

Table 16.--contInued
CROP2
. b
1ncome
B
B
B
S
R
R
R
W
W
1
5
6
4
REGION
4
5
6
1
6
200
0.18033
. 0.17914
0.60608
0.81052
0.20707
0.18441
2.77205
0.00705
0.00022
400
0.04508
0.04473
0.15152
0.20263
0.05177
0.04610
0.69301
0.00176
0.00006
600
0.02004
0.01990
0.06734
0.09006
0.02301
0.02049
0.30801
0.00078
0.00003
800
0.01127
0.01112
0.03788
0.05066
0.01294
0.01153
0.17325
0.00044
0.00001
\J3
1000
0.00721
0.00717
0.02424
0.03242
0.00828
0.00738
0.11088
0.00028
0.00000
CO
1200
0.00501
0.00498
0.01684
0.02551
0.00575
0.00512
0.07700
0.00020
0.00000
1400
O.OO368
0.00366
0.01237
0.01654
0.00423
0.00376
0.05658
0.00014
0.00000
1600
0.00282
0.00280
0.00947
0.01266
0.00324
0.00288
0.04331
0.00011
0.00000
1800
0.00223
0.00221
0.00748
0.01001
0.00256
0.00228
0.03422
0.00009
0.00000
2000
0.00180
0.00179
0.00606
0.00811
0.00207
0.00184
0.02772
0.00007
0.00000
2200
0.00149
0.00148
0.00501
0.00670
0.00171
0.00152
0.02291
0.00006
0.00000
2400
0.00125
0.00124
0.00421
0.00563
0.00144
0.00128
0.01925
0.00005
0.00000
aC, B, S, R, and W represent corn, beans, sorghum, rice, and wheat, respectively,
b, „ .
In quetzales per year.

Table 17---Area elasticities of market supply for each basic grain or association by regions of Guatemala
.. b
Area
C-B
C-B
C-B
C-S
CROP3
C-B-S
C
C
C
C
C
REGION
1
5 .
6
6
6
1
3
4
5
6
0.25
26.6378
11.5033
20.1198
37.2782
82.7982
11.7845
51.5516
23.2446
6.6568
0.9286
0.50
6.6595
2.8758
5.0300
9.3195
20.6995
2.9461
12.8879
5.8!11
1.6642
0.2321
0.75
2.9598
1.2781
2.2354
4.1420
9.1998
1.3094
5.7280
2.5827
0.7396
0.1032
1.00
1.6649
0.7190
1-2575
2.3299
5.1749
0.7365
3.2220
1 .4528
0.4161
0.0580 0
1.25
1.0655
0.4601
0.8048
1.4911
3.3119
0.4714
2.0621
0.9298
O.2663
0.0371
1.50
0.7399
0.3195
0.5589
1.0355
2.3000
0.3274
1.4320
0.6457
0.1849
0.0258
1.75
0.5436
0.2348
0.4106
0.7608
1.6898
0.2405
0.0521
0.4744
0.1359 â– 
0.0190
2.00
0.4162
0.1797
0.3144
0.5825
0.2937
0.1841
0.8055
0.3632
0.1040
0.0145
2.25
0.3289
0.1420
0.2484
0.4602
1.0222
0.1455
0.6364
0.2870
0.0822
0.0115
2.50
0.2664
0.1150
0.2012
0.3728
0.8280
0.1179
0.5155
0.2325
0.0666
0.0093
2.75
0.2202
0.0951
0.1663
0.3081
0.6843
0.0974
0.4261
0.1921
0.0550
0.0077
3.00
0.1850
0.0799
0.1397
0.2539
0.5750
0.0818
0.3580
0.1614
0.0462
0.0065
3.25
0.1576
0.0681
0.1191
0.2206
0.4900
0.0697
0.3050
0.1375
0.0394
0.0055
3-50
0.1359
0.0587
0.1027
0.1902
0.4224
0.0601
0.2630
0.1186
0.0340
0.0047
3-75
0.1184
0.0511
0.0894
0.1657
0.3680
0.0524
0.2291
0.1033
0.0296
0.0041
A. 00
0.1041
0.0449
0.0786
0.1456
0.3234
0.0460
0.2014
0.0908
0.0260
0.0036
CROP3
. b
Area
B
B
B
S
R
R
R
W
W
REGION
1
5
6
4
4
5
6
1
6
0.25
21.0788
1.0243
8.3482
3.5793
1.2037
18.6695
2.7164
1.0725
1.5142
0.50
5.2696
0.2561
2.0871
0.8948
0.3009
4.6674
0.6791
0.2681
0.3786
0.75
2.3421
0.1138
0.9276
0.3997
0.1338
2.0744
0.3018
0.1192
0.1683

Table 17.--cont¡nucd
, b
Area
B
B
B
S
CROP3
R
R
R
W
W
1
5
6
4
REGION
4
5
6
1
6
1.00
1.317*»
0.0640
0.5218
0.2237
0.0752
1.1669
0.1698
0.0670
0.0946
1.25
0.8432
0.0410
0.3339
0. 143?.
0.0482
0.7468
0.1087
0.0429
0.0606
1.50
0.5885
0.0285.
0.2319
0.0994
0.0334
0.5186
0.0755
0.0298
0.0421
1.75
0.4302
0.0209
0.1704
0.0731 â– 
0.0246
0.3810
0.0554
0.0219
0.0309
2.00
0.3294
0.0160
0.1304
0.0559
0.0188
0.2917
0.0424
0.0163
0.0237
2.25
0.2602
0.0127
0.1031
0.0442
0.0149
0.2305
0.0335
0.0132
0.0187
O
2.50
0.2108
0.0102
0.0835
0.0358
0.0120
0.1867
0.0272
0.0107
0.0151
2.75
0.1742
0.0085
0.0690
0.0296
0.0099
0.1543
0.0225
0.0089
0.0125
3.00
0.1464
0.0071
0.0580
0.0249
0.0084
0.1297
0.0189
0.0075
0.0105
3.25
0.1247
0.0061
0.0494
0.0212
0.0071
0.1105
0.0161
0.0064
0.0090
3.50
0.1076
0.0052
0.0426
0.0183
0.0061
0.0953
0.0139
0.0055
0.0077
3.75
0.0937
0.0046
0.0371
0.0159
0.0054
0.0830
0.0121
0.0048
0.0067
A. 00
0.0823
0.0040
0.0326
0.0140
0.0047
0.0729
0.0106
0.0042
0.0059
aC, B, S, R, and W represent corn, beans, sorghum., rice, and wheat, respectively.
k|n hectares.

Table 18.--Price elasticities of market supply for each basic grain or association by regions of Guatemala
Priceb
C-B
C-B
C-B
C-S
CROP3
C-B-S
C
C
C
C
C
REGION
1
5
6
6
6
1
3
4
5
6
0.03
4.1456
2.5377
2.9683
0.9518
5.2576
8.0228
0.0652
0.3143
1.4617
4.5938
0.06
1 .0364
0.6344
0.7421
0.2380
1.3144
2.0057
0.0163
0.0786
0.3654
0.1484
0.09
0.4606
0.2820
0.3298
0.1058
0.5842
0.8914
0.0073
0.0349
0.1624
0.5104
0.12
0.2591
0.1586
0.1855
0.0595
0.3286
0.5014
0.0041
O.OI96
â–  0.0914
0.2871
—
0.15
0.1658
0.1015
0.1187
0.0381
0.2103
0.3209
0.0026
0.0126
0.0585
O.I838
O
0.18
0.1152
0.0705
0.0825
0.0264
0.1460
0.2229
0.0018
0.0087
0.0406
0.1276
0.21
0.0846
0.0518
0.0606
0.0194
0.1073
0.1637
0.0013
0.0064
0.0298
0.0938
0.24
0.0648
0.0397
0.0464
0.0149
0.0822
0.1254
0.0010
0.0049
0.0228
0.0718
0.27
0.0512
0.0313
0.0367
0.0118
0.0649
0.0991
0.0008
0.0039
0.0181
0.0567
0.30
0.0415
0.0254
0.0297
Ó.Ó095
0.0526
0.0802
0.0007
0.0031
0.0146
0.0459
0.33
0.0343
0.0210
0.0245
0.0079
0.0435
0.0663
0.0005
0.0026
0.0121
0.0380
0.36
0.0289
0.0176
0.0206
0.0066
0.0365
0.0557
0.0005
0.0022
0.0102
0.0319
0.33
0.0245
0.0150
0.0176
0.0056
0.0311
0.0475
0.0004
0.0019
0.0087
0.0272
0.42
0.0212
0.0130
0.0151
0.0049
0.0268
0.0409
0.0003
0.0016
0.0075
0.0234
CROP3
Priceb
B
B
B
S
R
R
R
W
W
REGION
1
5
6
4
4
5
6
1
6
0.03
38.2024
1.8852
15.3889
0.1224
1.3742
0.0693
1.4777
1.9397
0.6075
0.06
9.5506
0.4713
3.8472
0.0306
0.3435
0.0173
0.3694
0.4849
0.1519
0.09
4.2447
0.2095
1.7093
0.0136
0.1527
0.0077
0.1642
0.2155
O.OÓ75
0.12
2.3877
0.1178
0.9618
0.0077
0.0859
0.0043
0.0924
0.1212
0.0380

Table 18.—continued
n • b
Price
B
B
B
S
CROP3
R
R
R
W
W
REGION
1
5
6
k
*4
5
6
1
6
0.15
1.5281
0.075**
0.6156
0.00*49
0.0550
0.0028
0.0591
0.0776
0.02*43
0.18
1.0612
0.052*4
0. *(275
0.003*4
0.0382
0.0019
0.0*41 1
0.0539
0.0169
0.21
0.7796
0.0385
0.31*41
0.0025
0.0280
0.001*4
0.0302
0.0396
0.012*4
—
0.2 *4
0.5969
0.0295
0.21405
0.0019
0.0215
0.0011
0.0231
0.0303
0.0095
N>
0.27
0. 716
0.0233
0.1900
0.0015
0.0170
0.0009
0.0182
0.02*40
0.0075
0.30
0.3820
0.0189
0.1539
0.0012
0.0137
0.0007
0.01*48
0.019*4
0.0061
0.33
0.3157
0.0156
0.1272
0.0010
0.01 1*4
0.0006
0.0122
0.0160
0.0050
0.36
0.2653
0.0131
0.1069
0.0009
0.0095
0.0005
0.0103
0.0135
0.00*42
0.39
0.2261
0.0112
0.0911
0.0007
0.0081
0.000*4
0.0087
0.0115
0.0036
Q.k2
0.19*t9
0.0096
0.0785
0.0006
0.0070
0.000*4
0.0075
0.0099
0.0031
3C, B, S, R, and V, represent corn, beans,sorghum, rice, and wheat, respectively.
k|n quetzales per kilogram.

Income (quetza1es/year)


Price (quetzales/kg)

106
Regression Coefficients
The regression coefficients of the five equations empirically
tested for the associations, behave in general as hypothesized. Total
family income (Y.), except for corn-sorghum in R£ and for corn-beans
i b
in R,., presents high levels of statistical significance. Total farm
size (A.) is less significant for corn-beans in R^_ and corn-sorghum
in Rj. than for the remaining associations. Quantity demanded on the
farm (l.) shows marginal statistical signifi canee for corn-beans in
Rj. and high significance for the remaining enterprises. Price (P.),
as expected for traditional crops, appears with the lowest level to
no statistical significance.
Due to the reciprocal nature of the specification, the negative
sign for total family income (Y.), farm size (A.) and price (P.) sig¬
nals the presence of a direct relationship between each of these vari¬
ables and the dependent variable. Only total income in the corn-beans-
sorghum equation of R^ has an unexpected sign. Of the three associa¬
tions in R^, corn-beans-sorghum seems to be the most traditional, which
may explain the unexpected sign. Surplus in this case may be in fact
inversely related to total income because higher-income farmers do not
cultivate this association.
The three remaining variables, education (E.), distance to the
nearest market (D.), and the relative profitability ratio (W.) provide
minor contributions to the model. All education coefficients are posi¬
tive; it is expected that as the level of education increases farmers

107
become more involved in the activities of the monetary economy and,
as a result, market more of their output. Levels of statistical
significance for education, when present, are very low except for
corn-beans in R^.
Distance to the market (D.) presents no statistical significance
in the corn-beans equations of R^ and R^, minor levels of significance
in the corn-sorghum and corn-bean-sorghum equations of R^, and a high
level of statistical significance in the corn-beans equation of R^.
Distance coefficients alternate with positive and negative signs.
Although a negative sign is expected, it is possible that the numerous
middlemen arriving with their trucks several times a month at different
places in rural Guatemala tend to eliminate a negative relationship
between surplus and distance. Distance in the data used for this
research, however, was defined as the distance to the place where the
family most commonly buys and sells, which may or may not refer to the
place where they sell the specific grain.
In the relative profitability ratio (W.), high levels of statis¬
tical significance are found in the corn-beans equation of R^ and in
the corn-sorghum equation of R^, and none in the remaining equations.
A positive sign for the corn-beans association ir. both R^ and R^_ is
expected. Since corn-beans is the basic subsistence cropping pattern
in Rj and R^ with only one commercial crop in the numerator of the
ratio for each region, the ratio and the surplus should move in the
same direction. Wheat and rice, respectively, are the commercial

108
crops in Rj and R^. In R^ three associations with both commercial
and traditional crops in the numerator of the ratio provide confusing
results evidenced by a positive sign for corn-sorghum and negative
signs for (W.) in the remaining two associations.
Income-Quantity Relationships
As expected, the income elasticities of market supply indicate
that all of the associations are quite responsive at very low levels
of income (Table 16). The responsiveness, however, decreases sharply
as income rises, which is an easily explained phenomenon. Farmers at
subsistence experiencing an income increase devote new resources to
production and react by marketing the newly created surplus. At
higher income levels, however, responsiveness tends to decrease
abruptly for traditional crops andonee the home use requirement is
met, commercial crops enter the production system. Figure 8 illustrates
that process and corroborates the conceptual model by displaying the
same pattern of behavior for all the associations in the different
regions of the country. That is, their appearance at almost zero income,
their elastic portions at low income levels, and their almost vertical
shapes at higher levels of income, are characteristics that were hypo¬
thesized in chapter three for those crops belonging in the traditional
category.

109
Farm Size-Quantity Relationships
Farm size elasticities (Table 17) and farm size-quantity relation¬
ships (Figure 9) for the associations parallel the income elasticities and
income-quantity relationships except for the corn-beans-sorghum enterprise
in Rg. In the case of farm size elasticities, as hypothesized, responsive¬
ness is more accentuated for traditional crops than for commercial crops at
low levels of farm size. The corn-beans-sorghum association of Rg presents
an elastic portion up to 2.25 hectares, a level much higher than the re¬
maining enterprises, perhaps due to the importance of sorghum as part of the
human diet in Rg. The vertical nature of the functions beyond low levels of
farm size, further corroborates the traditional presentation of chapter
three.
Price-Quantity Relationships
Associated enterprises, being the traditional subsistence cropping pat¬
tern, present very little price responsiveness (Table 18 and Figure 10).
All associations show a higher response at low price levels than at higher
prices and this finding is most accentuated in Rg with corn-beans-sorghum.
Mo available surplus at the end of the season when prices are high may con¬
tribute to this result as illustrated in Figure 5 (A) where Q^ shifts to
the left during the marketing period.
Corn
In terms of acreage, corn is the most important basic grain in Guate¬
malan agriculture. Besdies appearing in al 1 associations, corn is culti¬
vated as a single crop in all regions of the country. The dual character
of this enterprise, being both traditional and commercial, is shown by the
regression coefficients (Table 14 and Table 15), and the income, farm size,
and price elasticities of market supply (Table 16 to Table 18). The

110
income-quantity (Figure 11), farm size-quantity (Figure 12), and price-
quantity relationships (Figure 13) uphold the former finding and support
the basic theory of chapter three.
Regression Coefficients
Total income,total farm size, and quantity demanded on the farm carry
the expected signs in all of the corn equations. Except for farm size in R^
and for quantity demanded on the farm, all of the coefficients present high
levels of statistical significance. The price variable, however, displays
the highest levels of significance in Rj, R^, and R^ but also unexpected
signs. The opposite occurs in R^ and R^ where price carries the expected
sign along with no' statistical significance.
Education shows the expected positive sign in all corn producing regions
with the exception of R^ but marginal significance in R^ and the highest level
of statistical significance in R^. Distance to the market is only significant
in Rj and R^ but carry opposite signs, possibly for the same reasons as given
for the associations. The relative profitability ratio shows no significance
in Rj., low in R^ , and high levels of statistical signifiance in the remaining
three regions. The signs of the ratio vary according to the traditional or
commercial nature of the crop and to the nature of the remaining crops grown
in the region. In R^ corn is traditional and in R^ both traditional and: com¬
mercial, both having basically only commercial crops in the numerator of the
ratio. Given these characteristics it is anticipated that the ratio and the
dependent variable move in the same direction because self-sufficiency is not
secured. Corn, being both traditional and commercial in R^ and basically the
only crop in the region (only a few observations of commercial crops are in
the numerator) carries a negative sign possibly signaling that farmers, as

Income (quetza1es/year)
Quantity (1000 kgs)
Figure 11.Income-quantity relationships for corn by regions of Guatemala

Total Farm Size (ha)
2-5
2.0
1.5
1.0
.5
600 1200 1800 2400 3000 3600 4200 4800 5400 6000
Quantity (kgs)
Figure 12.—Farm size-quantity relationships for corn by regions of Guatemala
0
112

Figure 13•--Price-quantity relationships for corn by regions of Guatemala

self-sufficiency is secured, decrease corn marketing and shift into more
profitable crops. In , both commercial and traditional crops appear in
the numerator; for that reason, an inverse relationship is present. Finally,
R, presents an unexpected sign compared to Rr where the crop has the very
b 5
similar characteristics.
Income-Quantity Relationships
The income elasticities (Table 16) and the income-quantity relationships
illustrated in Figure 11 reveal the traditional nature of corn in R^, R^, and
R^, and an accentuated tendency toward commercialization in R^ and R^. At
very low income levels, corn is quite income responsive. The responsiveness
tends to decrease more rapidly in R^, R^, and R^ as a result of the tradi¬
tional nature of the crop in these regions. In R^ and R^ though becoming in¬
elastic beyond the Q200 per year level, corn still shows some responsiveness
at higher income levels. This responsiveness may be due to the diversity of
chemical input usage, a situation only possible at high income levels, as
identified in the production and distribution activities in chapter four.
Furthermore, the fact that commercial sales (Q.) begin around the Q150 income
level denotes the subsistence character of this crop in these two regions at
very low income levels.
The dual role of corn in R^ and R^ is corroborated by a higher level of
home use relative to the other regions. In these two regions, corn is culti¬
vated as a single crop only, as opposed to the other regions where it also
appears in all of the basic grain associations.
Farm-Size Quantity Relationships
Findings from the farm size elasticities (Table 17) and the farm size-
surplus relationships (Figure 12) closely parallel those of income. R^ and
R^ again display the traditional and commercial nature of corn.

115
R,, R_, and R, grow corn mainly for subsistence. At low levels of farm
I 5 fa
size, all crops are highly responsive, with the responsiveness decreasing
faster in R^, R,., and R^ than in R^ and R^. The vertical shape of the
functions in the former three regions means that subsistence may be
secured and, since the crop is not commercialized, production and mar¬
keting decrease.
The subsistence character of corn in R^ is given by its production
at near zero farm size but sales of corn commence beyond the 0.^5 hectare
size. The same reasoning applies to R^, where production takes place
at almost zero farm size but marketing occurs only when farm size exceeds
0.25 hectare. These findings closely parallel the theoretical presen¬
tation of chapter three.
Price-Quantity Relationships
Though price elasticities for all regions are computed (Table 18),
only price-quantity relationships for R^ and R^ are graphed (Figure 13)
because unexpected signs appear in the remaining regions. In R^ and R^,
corn is minimally price responsive despite i ts commercial nature. Being
less responsive in R^ than in R^ may result from prices being relatively
lower than expected as evidenced by the heavy dependence on stored seed
(95 percent of total seed used). Low prices may induce farmers to with¬
hold more production than anticipated.
The unexpected price sign for corn in R^, R,., and R^ can be explained
with the conceptual model of chapter three. Available output decreases
throughout the marketing period as prices increase. Near to the

116
asymptotic section of the pri ce-income-consumption (PIC) path, higher
prices may have resulted in decreasing quantities marketed, thereby
leading to the indirect relationships observed between price and the
surplus-output ratio.
Beans
Beans are cultivated as single crops in R., Rr, and R¿, where they
I 5 b
also appear associated with other basic grains. This crop shows the
behavior of a traditional enterprise, as given by the regression coef¬
ficients (Table 14 and Table 15), the income, farm size, and price
elasticities (Table 16 to Table 18), and the income-quantity relation¬
ships (Figure 14).
Regression Coefficients
All income coefficients in the three bean equations present the
expected negative sign and high levels of statistical significance.
Regression coefficients for the total farm size variable are also sig¬
nificant at high levels but present the expected sign only in R^. Un¬
expected signs in R^ and R^ may be the result of omissions committed
at the time of data collection, as has been recognized by AID officials
(see chapter six), when interviews failed to specify some crops that
were interplanted. Quantity demanded on the farm shows the expected
sign in all equations, with a high level of statistical significance
in R^, less significance in R5 and none in R^. The price variable,
showing different levels of statistical significance, carries unexpected
signs in all three equations.

Income (quetza1es/year)
Quantity (kgs)
Figure 14. — Income-quantity relationships for beans by regions of Guatemala

118
Education carries an unexpected sign in R^ , low levels of statis¬
tical significance in Rj and R^ and none in R^. Distance being barely
statistically significant in R^, carries an unexpected positive sign
in Rj and R^., possibly due to the role of truckers and middlemen ex¬
plained in the discussion of the associations.
The relative profitability ratio is only statistically significant
in R^ and expected negative signs are present in R^ and R^. Since beans
are traditional crops and both traditional and commercial crops appear
in the numerator, an inverse relationship between the ratio and the
dependent variable is correct. For the same reasons, the positive sign
in Rj. can be regarded as unexpected.
Income-Quantity Relationships
The income elasticities (Table 16) and the income-quantity rela¬
tionships (Figure 1¡4) for beans show the traditional character of this
enterprise. Beans present some income responsiveness at very low income
levels, but as income increases the functions become almost perfectly
inelastic as in R, and Rr above the Q50 level, and in R¿ above the Q150
1 5 o
1evel.
Farm Size-Quantity Relationships
No farm size-quantity relationships are depicted for beans since
comparisons are not possible because only one correct sign is present.
Farm size elasticities for R^ illustrate very little responsiveness
(Table 17). Unitary elasticity is found at the 0.25 hectare farm size
level and thereafter, elasticities decrease sharply. At that point,
other crops may enter the production system.

119
Price-Quantity Relationships
Price elasticities of market supply (Table 18) for beans are
discussed without a graphical presentation because the price signs
are negative in all three equations. The unexpected price sign
can be explained as in the case of corn. A wide price range for
beans prices, possessing the highest prices of all basic grains in
the sample, strongly corroborates the reasoning behind the concep¬
tual model. Increasing prices during the marketing period up to
the asymptotic section of the PIC path may have resulted in marketed
output reductions.
Sorghum
Sorghum is only grown as a single crop in R^. Regression coef¬
ficients (Table lA and Table 15) and income, farm size, and price
elasticities of market supply (Table 16 to Table 18) reveal a tradi¬
tional crop with some degree of commercialization. Income, farm size,
and price relationships are not depicted since no comparisons are
possible.
Regression Coefficients
Total family income and quantity demanded on the farm conform
to expectations regarding sign and level of statistical significance.
Total farm size and price present neither the expected sign nor a
level of significance. Education and distance, with minor statisti¬
cal significance, carry unexpected signs. The relative profitability
ratio presents the highest level of significance relative to the other

120
variables in the sorghum equation and the correct sign; since sorghum
is both a traditional and a commercial crop, with other crops of both
types in the numerator, a direct relationship is expected.
Income-Quantity Relationships
Income elasticities (Table 16) reveal that sorghum is a very
income responsive crop at low income levels, with the responsiveness
decreasing as income increases. Since sorghum in this region is
mostly sold to livestock feed processors, becoming a highly commercial
crop, the elastic portion of the curves, located at very low levels of
income, may reveal that farmers with low income levels are the main
suppliers.
Farm Size-Quantity Relationships
The total farm s.ize coefficient presents an unexpected sign, a
condition possibly related to the income responsiveness situation. If
farmers at low income levels are the main suppliers to feed processors
in the region, it is natural that, as the size of the farm and income
increase, there is a tendency to reduce production thereby providing a
basis for the indirect relationship between farm size and market supply
Price-Quantity Relationships
The likely presence of traditional and commercial farmers in the
sample may have produced the unexpected price sign. The limited number
of observations for low quantities at high price levels might have
caused the discrepancy by making the function slope in the opposite
direction.

121
Ri ce
This basic grain is cultivated mainly in R^, R^, and R^. The
regression coefficients (Table 14 and Table 15), the income, farm
size, and price elasticities of market supply (Table 16 to Table 18),
and the income-quantity (Figure 15) and farm size-quantity relationships
(Figure 16) give strong support to the conceptual model of traditional
and commercial supply response. In the case of rice, the land con¬
straint plays an important role in shaping the appropriate charac¬
teristics for the crop.
Regression Coefficients
All coefficients of total family income and quantity of rice de¬
manded on the farm present the expected sign and high levels of statis¬
tical significance. Total farm size shows the expected sign in R^ and
R^, and is statistically significant only in R^. The price coefficient
is statistically significant in R^ and R^, with unexpected signs, and
is not significant in R^ where it carries the expected sign.
Education shows the expected positive sign in all three equations
but is not statistically significant in R^. Distance to the market for
rice producers carries positive signs in R^ and R^ and a negative sign
in R^ while statistical significance varies from none in R^_ and low in
R^ to high in R^.
The relative profitability ratio for rice shows more statistical
significance in R^ than in R^ and none in R^. Positive signs in R^
and R^ are expected. Since this is a commercial crop with subsistence
crops in the numerator of the ratio, a direct relationship is normal.

Income (quetza1es/year)
Figure 15. " Income-quantity relationships for rice by regions of Guatemala
122

Total Farm Size (ha)
Quantity (kgs)
Figure 16. — Farm size-quantity relationships for rice by regions of Guatemala

124
With self-sufficiency secured, farmers can move
product ion. Háving the same characteristics in R
a negative and unexpected sign.
5
into commercial-crop
, the ratio presents
Income-Quantity Relationships
Appearing when basic income levels have been attained, rice shows
some income repsonsiveness at low income levels with the response de¬
creasing less rapidly than for traditional crops. This behavior is
substantiated by the income elasticities of market supply (Table 16)
and the income-quantity relationships (Figure 15). The former charac¬
teristics follow exactly the description of commercial crops in the
conceptual model. Low levels of home use further accentuate the com¬
mercial nature of rice in the three regions.
Farm Size-Quantity Relationships
The farm size elasticities for rice (Table 17) and the farm size-
quantity relationships (Figure 16) strongly support the reasoning behind
che theoretical presentation of chapter three. They also emphasize the
major enterprise differences prevailing among regions, sub-regions, and
even, departments in Guatemala.
Rice is, no doubt, a highly commercial crop in R^. Cultivated
mainly in the Zacapa area, where land is available, the rice relation¬
ship displays the shape of a commercial crop, supported by a relatively
wide range in the elastic response and a minor amount (3 percent) of
total production for home use. In R^, however, rice is grown primarily
in the Jutiapa area by taking advantage of small pockets of suitable

125
soil. Once those pockets are under production, enlargement of the
farm will not influence rice production, or in other words, the rice
land constraint has been reached. For those reasons, farm size-quan¬
tity relationships for rice assume the shape of a commercial crop in
Rr and of a traditional crop in R¿.
5 b
The unexpected sign found for the farm size and rice supply
relationship in R^ can also be explained in terms of the land constraint
In the conceptual model, it was said that, as income rises, with self-
sufficiency guaranteed, farmers tend to diversify production by growing
high value crops until the land constraint is reached. In R^, besides
the basic grains under consideration, plantain, sesame, and coffee are
also present. These crops may offer farmers a better alternative as
farm size becomes larger and cause rice production to vary inversely
with farm size.
Price-Quantity Relationships
Price elasticities of supply for rice (Table 18) are discussed
without the illustration of price-quantity relationships. The presence
of only one expected sign eliminates comparisons among the three regions
Rice production in R^ shows the typical farmer response moving
gradually up and along the PIC path as presented in chapter three. R^
and Rj_, however, reveal the same negative relationships encountered for
several'! other crops. In this case, higher prices with low quantities
near the asymptotic portion of the PIC path are explained by the limited

126
surplus available just prior to planting time when rice seed prices
soar tremendously. By this time, farmers '.cannot'. react strongly to
high prices since they have been moving upward along the PIC path
during the year.
Wheat
Wheat is produced and marketed in R^ and R^. Regression coef¬
ficients (Table 1^4 and Table 15), income, farm size, and price elas¬
ticities (Table 16 to Table 18), and farm size-quantity relationships
(Figure 17) reveal a commercial crop whose behavior, heavily influenced
by the governmental price support program, is contrasting in both
regions.
Regression Coefficients
While total family income for wheat presents the expected sign and
the highest level of statistical significance in R^ , it shows neither
characteristic in Rg. Total farm size displays the expected sign in
both equations but is more statistically significant in Rj than in R^.
Quantity demanded on the farm, with the highest level of statistical
significance, presents the expected sign in both regions. Price carries
the expected sign in Rj and R^ but is of lower statistical significance
in the former than in the latter.
Education, being more statistically significant in R^ than in R^,
carries an unexpected sign on the latter. Distance to the market rela¬
tive to wheat supply shows a positive sign in R^ and a negative sign in
R^ and no level of statistical significance in either.

Total Farm Size (ha)
Figure 17*__Farm size-quantity relationships for wheat by regions of Guatemala

128
The relative profitability ratio presents high levels of statistical
significance and the expected signs in both wheat producing regions.
The positive sign in R^ implies that as the ratio (return per hectare
in all crops except wheat divided by the return per hectare in wheat)
increases, the surplus-output ratio is expected to increase. The numera¬
tor in this case includes some subsistence crops while wheat in the de¬
nominator is commercial. Having secured self-sufficiency, farmers can
afford to grow commercial crops where risk is minimal as is the case of
wheat. This case illustrates the typical subsistence region described
in the conceptual model. The negative sign in R^ is as expected since
there are traditional and commercial crops in the numerator of the ratio.
Rice, for example, may well be a better alternative than wheat in a
region as commercial as R^.
Income-Quantity Relationships
The traditional nature of R^ as opposed to more commercialized
wheat production in R^ is very well documented by the income elasti¬
cities of market supply (Table 16). V/heat is a commercial crop in both
regions. However, wheat supply does present very little income respon¬
siveness in R^ and the opposite sign in R^. In support of the conceptual
model, traditional farmers in Rj, once self-sufficiency has been secured,
grow a little wheat which provides a relatively secure source of income.
The weak income responsiveness may be caused by the price support program
Although no quantity restrictions have been imposed, the price support
is also a ceiling price and may be viewed as a limit on producer revenues

129
beyond which higher value crops may become a better alternative. Be¬
cause more commercialized regions display a stronger tendency to move
into higher value crops, R^ carries a negative sign for the income
variable.
Farm Size-Quantity Relationships
Farm size elasticities (Table 17) and farm size-quantity relation¬
ships (Figure 17) further support the statements of the former section.
In both regions, the elastic response is minimal up to the 0.25 hectare
size, beyond which the responsiveness decreases sharply. Besides the
reasons explained above, this reaction could be the result of the heavy
use of chemical inputs discussed in chapter four. Intensive application
levels and consequent yield increases may be the same as devoting more
land to wheat production when land becomes avilable through the use of
new technology.
Price-Quantity Relationships
Price-elasticities of market supply (Table 18) reveal that wheat
production is minimally responsive to price changes. Wheat producers
probably behave in this manner as a result of the price support program.
Summary
An analysis of the traditional and commercial supply response by
producers of basic grains was accomplished by estimating and studying
the regression coefficients and the respective elasticities for basic

130
grains in five regions of Guatemala. Explanations for the behavioral
characteristics identified provide support for the theory as expressed
in an earl ier chapter. Careful attention, however, must be given to
generalizations based on these results. The following chapter will
pursue the general implications of the descriptive and regression
analyses.

CHAPTER VI
SUMMARY, CONCLUSIONS, IMPLICATIONS AND RECOMMENDATIONS
This chapter contains a brief description of why a study of
traditional and commercial farm supply response was undertaken,
and the objectives necessary to adequately investigate the problem
related thereto for Guatemala. Research findings and their impli¬
cations are presented. Without a thorough examination and presen¬
tation of these results, little will be gained in the quest for a
better understanding of traditional and commercial supply response.
Thus, this chapter draws conclusions and proposes recommendations
based upon the implications derived from the empirical results. A
special section is devoted to discussing some data problems encountered
in the research and how they may have affected the results.
Problem and Objectives
Characteristics portraying Guatemala as a developing country in¬
clude: a rapily growing population, two-thirds of which is employed in
the agricultural sector; a limited arable land base; and many farmers
living in poverty conditions, with high rates of unemployment, and
very low levels of food production. For these reasons, the country's
131

132
development efforts are concentrated on the implementation of programs
designed to more intensively utilize land, to reduce unemployment, and
to increase production and productivity in rural areas.
Work at the Institute of Agricultural Science and Technology (ICTA)
of Guatemala is focused on subsectoral programs intended to develop new
technology. The quest for technology is aimed at generating productivity
increases, especially in basic grains, to enable the country to meet its
requirements without increasing the land area committed to production.
Productivity advances, however, may create two different problems.
First, small farmers, discouraged by the erratic behavior and low level
of basic grain prices, may utilize the new technology to produce the
same amount of grains on less land and devote the unused as well as new
land to the production of other crops. This has been observed recently
in some areas of the country. Second, if farmers utilize the new tech¬
nology on all of their land, the so called "second generation marketing
problems" are likely to appear.
Since it becomes important to understand the traditional and com¬
mercial farm supply response as a basis for policies focused on both
of these problems, the main objective of this study was to estimate
market supply functions for each basic grain or association in the
different regions of Guatemala. Other objectives were to compute the
corresponding income, farm size, and price elasticities of market
supply and to delineate and quantify production-distribution activities
for basic grains in the different regions of the country. A Small

133
Farmer Credit Survey conducted by the Government of Guatemala and the
Agency for International Development (AID) in 197^ provided the data
necessary to accomplish these objectives.
In general, it was hypothesized that, income, farm size, and price
elasticities of market supply for both traditional and commercial basic
grains are high at very low levels of income, farm size, and price, re¬
spectively. But at higher income, farm size, and price levels they tend
to become almost completely inelastic for traditional crops but somewhat
less inelastic for commercial crops. To test these hypotheses, market
supply equations for each single crop and associated crop enterprise
were estimated separately in each region of the country. It was also
hypothesized that if the productivity and production of basic grains can
increase, production and distribution activities seem to be adequate.
To test this hypothesis, production and distribution activities were
delineated and quantified. The results obtained are summarized in the
fol lowing isection.
Research Findings
Results found in the delineation and quantification of the produc¬
tion and distribution activities are discussed first followed by a
summary of findings concerning traditional and commercial farm supply
response.

134
Production and Distribution Activities
From the input standpoint, basic grain production is most influenced
by seed and fertilizer costs. While fertilizer use tends to be a general¬
ized practice, with the level of application depending upon crops and re¬
gions, pesticides and soil additives are not commonly utilized. Seed
management becomes dependent upon product sales, seed storage, and seed
purchase decisions. Thus, variation does prevail in the percentage of
total production set aside to be used as seed and animal feed and the
percentage of seed which is purchased. Regarding labor, corn, rice,
and wheat are the enterprises with the highest employment per hectare,
followed by beans and the associations. Except for the latter, where
employment per unit of land is very similar, all enterprises present
different levels of employment by region.
Total basic grain production differs among crops with respect to
yields and product distribution. Average production per unit of land
is very similar for each crop grown in different regions. However,
when the crops of the associations are grown as single crops, yield
decreases for beans while increasing for corn and sorghum.
Excluding wheat and rice, consumption per family is relatively
large and does not show major regional differences. Corn is the grain
most used for processing, sales "in kind," and donations, all of which
are not very generalized activities.
Variations found in cash sales are the result of differences in
farm demand for production and consumption purposes. The more tradi¬
tional the crop is, the lower will be sales. Expenditures incurred

135
in marketing of basic grains are generally one cent or less per kilogram.
When these expenditures are expressed as a percentage of the average
regional price and ranked from highest to lowest, the order is wheat,
rice, sorghum, corn, associations, and beans.
Traditional and Commercial Farm Supply Response
In general, estimated regression coefficients behave as hypothesized.
Total income, total farm size, and quantity demanded on the farm are
highly significant variables and, with few exceptions, show the expected
sign. Price presents different levels of statistical significance and
alternate signs. Education, distance, and the relative profitability
ratio provide a minor contribution to the model.
Traditional crops generally appear at near zero income levels
while commercial crops are cultivated when higher levels of income have
been attained. Income elasticities of market supply for both types of
crops are very responsive at low income levels. However, while commercial
crops still show some responsiveness at higher income levels, traditional
crops become almost perfectly inelastic. These findings corroborate the
theoretical presentation. That is, farmers at subsistence levels experi¬
encing income increases devote new resources to production and react by
marketing the newly created surplus. At higher income levels, respon¬
siveness tends to decrease sharply for traditional crops; once the home
use requirement is attained, commercial crops enter the production system.
Traditional crops pervade the basic grains spectrum in Guatemalan
agriculture. All of the enterprise associations, being the basic sub¬
sistence cropping pattern, belong in the traditional category. Corn is
Á

136
a traditional crop in R,, R , and R,, but becomes commercialized in
I b b
R^ and R^. Beans are traditional in all regions. Sorghum is both
a traditional and a commercial crop in R^. Rice displays the charac¬
teristics of a commercial crop in all three regions (R^, R^., and R^)
where it appears. Wheat in R^ is a commercial crop and is not highly
income responsive since it serves the purpose of providing farmers
with a relatively secure source of income at low income levels. At
higher levels of income, crops other than wheat may become a better
alternative. Although no quantity restrictions have been imposed, the
price support, by establishing both a minimum and a maximum price, may
be viewed as a ceiling on producer revenues. R^ supports the former
explanation; being a highly commercialized region, as opposed to R^
which is mainly a subsistence region, wheat presents the opposite
income sign in R^. Other commercial crops may have become more income
rewarding enterprises.
Total farm size elasticities closely parallel the income elasti¬
cities and also support the conceptual model. Traditional crops appear
at minimal farm sizes while commercial crops are grown as farm size
increases. Both traditional and commercial crops are very responsive
at low levels but while some farm size-supply responsiveness remains
at higher levels for commercial crops, it decreases sharply for tradi¬
tional crops once self-sufficiency is attained. Concerning farm size
elasticities, all crops can be cateogrized in the same way as those
for the income elasticities.
The price elasticities of market supply are generally very low
for both traditional and commercial crops. They show a higher response

137
to low price levels than to higher prices. Since farmers move up and
along the pri ce-income-consymption (PIC) path and the surplus decreases
during the marketing period, they can not react strongly to price
changes at the end of the season when prices are highest. The opposite
signs found for price in many of the equations can also be explained in
the same terms. Thus, it may be possible that, when prices are highest,
farmers have already arrived at the asymptotic section of the PIC path
and, therefore, higher prices w¡11 encounter a lower quantity marketed
response.
Data Generalizations and Implications
Descriptive statistics and statistical inference are used in this
study. Since the data come from a random sample and do not encompass
the entire population, two main assumptions are necessary to make in¬
ferences from the statistical results to the population. First, it is
assumed that the sample is representative of the true population and,
second, that 1973 was a typical year.
Both assumptions appear to be reasonable. As shown in chapter
one, the sample contains a sufficient number of observations of tradi¬
tional and commercial farms to draw safe conclusions at the regional
and national levels. Concerning the second assumption there are no
reasons to believe that 1973 was not a typical year. Furthermore, it
also has been proven in the appendix that the least squares estimators
of the regression coefficients are the best linear unbiased estimators
(BLUE) of al 1 1 i near unbiased estimators of the respective parameters.

133
Notwithstanding the above qualifications, the data display suffi¬
cient characteristics conducive to errors in the interpretation of
results to necessitate a discussion of these concerns before recom¬
mendations are made.
Errors and Omissions in Data Recording
Four errors in data recording related to the information used in
this study can be identified [ 10 6]. The first, and a very important one,
relates to lack of care by the interviewers in recording responses to
the question that deals with interplanted crops. Emphasis was not given
to recording which crops are interplanted and which of the interplanted
crops is the principal crop [I06,p. 79]- This omission is mainly re¬
flected in corn and beans in R. , Rr, and R¿. The second major data-
I b
recording error entails the distance variable where figures given in
meters or fractions were rounded to the nearest kilometer [106, p. 68].
For that reason, all entries start at the one kilometer level. Third,
not all physical losses were recorded, especially by farmers who consume
a relatively large share of their production [106, p. 77]- This error
appears in the very unlikely 1 percent average computed for losses in
all basic grains. Finally, interviewers were not consistent when re¬
cording production withheld by farmers for sale at future dates [106,
p. 77]- This situation, however, does not affect the results obtained
but it does support the theoretical model discussed in chapter three
since the model is based on the assumption that farmers save some
production to be sold throughout the marketing period.

139
To the errors and omissions just mentioned, can be added a question
in particular that was badly designed and other ommissions. When asking
to whom production was sold, it was only possible to check one, two,
three or any combination of alternatives but specific quantities sold
to each outlet were not obtained. This failure makes it impossible to
know the amount of basic grains going through the different marketing
channels whenever more than one channel was checked. The remaining
omissions relate to failures in specifying quantitative values for
several variables such as education, distance to the market, and quantity
demanded on the farm. A value equal to the mean was assigned to replace
these missing values only when regressing the corresponding equations.
Upward or Downward Bias
Descriptive statistics for the variables included in each of the
estimated equations are computed as a basis for discussing the introduc¬
tion of possible bias in the results. Minimum and maximum values, mean,
standard deviation, kurtosis, skewness, missing observations, and total
number of questTonrra'i res by region and crop are presented for each inde¬
pendent variable in Table A-l through Table A-7-'
Kurtosis refers to the relative peakness or flatness of a curve.
A value of zero indicates a normal distribution; a positive value means
a narrow (more peak) curve, while a negative value indicates a flatter
curve. For skewness, a zero value corresponds to a bell shaped dis¬
tribution; a positive value indicates clustering to the left of the
mean with most extremes values to the right, and a negative value
means the opposite. The remaining statistics and values are self-
explanatory .

Education of household Head
In general, the number of years of formal education is relatively
low in every case (Table A-2). Although the results obtained reveal
normal distributions in almost every case, some consideration should
be given to the occasionally large number of mi's-s:i.ng observat ions .
These observations were made equal to the mean when, in fact, failure
to report educational level might have been due to situations of lower
levels of education. The resulting small difference, however, should
not greatly affect the results.
Distance to the market
Besides the error leading to the one kilometer starting point for
all farms, there is no reason to believe that the results obtained for
this variable are not representative (Table A-4). A relatively small
number of missing observations does not present major problems of mis¬
leading data when set equal to the mean.
Total Farm size
Total farm size deserves special consideration. Since the main
purpose of this study is to draw inferences about traditional and
commercial farm supply response, size of farm becomes a good indicator
of the extent to which the data represent farmers involved in either or
both types of farming. Although size of farm has not been defined in
the present study, both extremes of the spectrum are not adequately
represented. Regression equations with a few relatively large farm
sizes, however, were included (Table A—3)• The highest mean values,

\k]
between 15 and 2k hectares, are localized in the corn equation of R^,
in the rice, corn, and beans equations of R^, and in the beans and corn-
beans equations of R.. However, the kurtosis and skewness statistics
6
computed reveal a positive sign for all the equations meaning both
narrow distributions and clustering to the left of the means with most
extreme values to the right of the mean, respectively. Thus the few
relatively high values do not appear to impose bias in the results
obtained. Their presence, however, is revealed and should be recognized
when interpreting results for those enterprises.
Total family income
Similar in importance to total farm size, this variable also reveals
in some of the equations, the presence of values higher than the non-
defined total family income (Table A~7)• Although total family incomes
of values higher than Q10,000 a year are found in several equations, mean
values are relatively low in all equations. The presence of a positive
sign in both kurtosis and skewness has the same implications here,
meaning the apparent upward bias in the data in these cases in not
creating difficulties.
Farmgate price
The price variable is important in the model. The values and
statistics computed stimulate some concern about the degree of validity
of the findings in several of the equations (Table A-l). All crops,
except wheat in R^, present a relatively large price range to permit
estimation of the equations. Standard deviations, on the other hand,

142
are relatively low to allow for estimation within comfortable limits
of confidence in most of the equations. A zero or minus sign in
kurtosis, signaling a normal or flatter distribution in prices is
only present in six of the equations. Besides these six, another
four equations diplay a skewness of zero portraying a bell shaped
distribution. All in all, inferences about price responsiveness are
valid in the ten mentioned equations; in the remaining nine some
consideration ought to be given to the distribution and properties
of the data in each case.
Quantity demanded on the'farm
Data in this variable do not seem to necessitate any special dis¬
tribution since values will vary according to family size and subsis¬
tence needs. Standard deviations, being quite large, support this
contention (Table A~5). Furthermore, missing observations replaced
by the corresponding mean values are relatively few thereby reducing
potential problems from this area of concern.
Relative profitability ratio
No special distribution is desired in this variable either. The
ratio will assume values according to the revenues per hectare obtained
from the different crops by each farmer. Values and statistics computed
seem to corroborate this contention (Table A-6). A word of caution
about the number of missing observations, however, seems appropriate.
Since missing observations in this case reveal some farmers growing
only that specific basic grain or association the missing values can

143
not be replaced by mean values since it is incorrect to attribute
unearned revenue to these farmers. Therefore, cases with relatively
high numbers of missing values are approached with caution when analyzing
the results obtained.
Conclusions and Recommendations
The alternative questions to which this study is addressed are as
follows: Do traditional farmers adopt the new technology being generated
by ICTA for basic grains to produce the same or less output on less land,
or do they make full use of the land and technology to augment basic
grain production? V/hat will be the consequences in each case?
The argument in support of the national policy objective to increase
basic grain production has been widely discussed in the development litera¬
ture. The reasoning is that, in a closed economy, food grain prices would
fall as a result of significant increases in production. However, lower
prices could still provide adequate incentives to farmers if much of the
increase is to due to cost-free technological change. Furthermore, with
substantial supplies of grain, the government can have much more expan¬
sionary fiscal and monetary policies which, if directed toward labor-in¬
tensive public projects, can shift the demand curve for grains, and
thereby help to counteract some of the decline in prices [32, p. 704].
In the case of Guatemala, demand elasticities for basic grains are not
known at any level of the marketing chain. Empirical studies conducted
in similar countries have produced inelastic demands. However, the
impossibility of estimating demand elasticities at the farm level in
this study gives rise to some concern. The problem seems to revolve

around the question of whether or not self-sufficiency has been attained
in certain regions of the country. Quantities marketed will therefore
vary accordingly since the magnitude of the elasticities will differ in
every case. Demand elasticities at the consumer level cause less con¬
cern. In general, the country is a net importer of basic grains and the
demand curve for these grains is elastic at the imported price; an in¬
crease in production would probably not drive prices down but would
instead bring beneficial effects to the economy. Since the world demand
for most basic grains is also elastic at the market price, the country
could export any available surplus not absorbed by the domestic market.
The question is solved therefore except for the unknown elasticities of
demand at the farm level and for the presence or lack of adequate faci¬
lities to market the increased production.
The remaining question is more complex. It has been shown that in¬
come, total farm size, and price elasticities of market supply are rela¬
tively high at low levels with the responsiveness decreasing at a rapid
rate for the subsistence crops and at a lower rate for the commercial
crops. Wheat, however, is an exception. At higher income levels, the
response functions become almost perfectly inelastic. Therefore, it
would appear that little hope prevails for the attainment of massive
increases in production of all basic grains. Some basic grains in some
regions seem to have a slight potential for increased production.
These are corn in and R^, and rice in R^ and R,.. But, in general,
the resulting increases would fall far behind the desired goal and
expectations of the Guatemalan government.

1*»5
Another relevant finding is an indication that traditional farmers
shift to commercial or high value crops once self-sufficiency has been
reached. Such shifting may cause serious repercussions. Marketing
facility needs for high value crops are in general more sophisticated
than for basic grains. These products display more possibilities for
damage, spoilage and price differences than basic grains. Therefore,
more sophisticated grades and standards, and transportation, handling,
packing, storage, and market information facilities are needed.
The above conclusions serve as a base for several recommendations:
First, seasonal demand studies at the farm and consumer levels are
necessary not only for basic grains but also for high value crops.
This would ease the quest for information about the prevailing and future
trends in conditions of demand and supply and thereby provide a basis
for developing a cropping pattern that would not distort the market
mechanism. Second, basic grain production should be emphasized in the
crops and regions presenting the higher probability of increasing pro¬
duction. By concentrating efforts in the specific crops and regions
where such increases are most likely, (corn in R^ and , and rice in
R^ and R^), greater accomplishment may be expected. Finally, it has
been inferred that, for the Guatemalan situation; basic and applied
research on basic grains alone will neither serve the small farmer's
needs entirely as he moves into higher value-higher risk crops nor
will it. serve the national production goals for basic grain. Further¬
more, there seems to be a contradiction between the objective of in¬
creasing basic grain production and the goal of overall development of
the country. If increases in average per capita income can not be

146
obtained for small farmers alone from the production of basic grains,
even if production targets are met, the goal of increased production
of basic grains contributes little to economic growth since the tradi¬
tional farm sector is the one most needing increases in income per
capita.
Thus, besides production research, careful consideration should
be given to various other alternative programs as incentive to stimu¬
lating production to meet national goals while fulfilling the risk
aversion and income criteria of traditional farmers. Because of the
somewhat diverging yet complementary behavior of traditional and
commercial crops on Guatemalan farms, research emphasis must also be
assigned to high risk crops along with basic crops. This research
must assume a farm system focus while avoiding isolated enterprise
evaluations if it is to be of use to small farmers and to meet the
production goals of the national government.

CHAPTER VI I
REFLECTIONS ON THE THEORY OF DEVELOPMENT
Introduction
....What we tend to forget, however,
is that the essential aspect of an
'underdeveloped' economy and the
factor the absence of which keeps it
'underdeveloped' is the ability to
organize economic efforts and energies,
bring together resources, wants, and
capacities, and so to convert a self-
limiting stat ic system into creative,
self-generating organic growth [28,
p. 335].
However, when the efforts are organized in reverse and the energies
and tasks are working toward unattainable goals, the limitations will
perpetuate themselves and the self-generating organic growth will never
materialize.
It is a reality that all developing countries, at some stage in
the development process, must face the issue of extracting a surplus from
agriculture while at the same time providing for public investments in
the agricultural and industrial sectors. But careful attention must be
given to fomenting the realization of a surplus where it is a real, not
imagined, possibility within limited resource conditions. A serious mis¬
judgement can lead to a waste of time and resources that might be used
147

more effectively. The opportunity cost for developing countries in
this case is extremely high.
The review of literature in chapter two reveals a theory of agri¬
cultural development constantly evolving since the end of World War II.
That the agricultural sector is to play a key role in the development
process is today widely accepted. The precise nature of this role and
pol.icies most appropriate to fulfill that role.whatever' it is, are not
fully agreed upon. One of the prescriptions most often followed has
been to emphasize increasing production of food crops per land and
labor unit by relying on modern y i eld-increasing technology. Yet both
productivity increases and stagnant or even declinrng production have
been observed in some of these countries. The reason for the disap¬
pointing results is the failure to analyze the total small farm or tra¬
ditional basic economic system.
This study has attempted to close that gap in the theory. Chapter
three has presented a conceptual model of the tojta.l basic economic system
for "traditional" or "small" farms. Owing to his subsistence needs, the
land constraint, and his income level, the traditional farmer's behavior
within his basic economic system is one of carefully balanced risk aver¬
sion, income maintenance,and risk taking. The results presented in
chapters four and five tend to validate the model. With the correspondin
adaptations the model can be useful for the analysis of the traditional
farm sector in different countries with varied single and associated
cropping patterns. The results of the model are now merged with the
three generation problems of the Green Revolution.

The Green Revolution: Generation Problems and
Small Farm Development
Three generation problems related to Green Revolution agriculture
have been explicitly delineated by Walter P. Falcon [32]. Research
findings from the present study in Guatemala further expand and to some
extent modify the implications of these problems.
First Generation
Production related problems, where great production successes have
been hampered by serious limitations, are included in the first group.
Constraints on adoption of new technology include, for example, lack
of adequate and controllable water supplies (without irrigation, fer¬
tilizer provides only a low return) and inadequacy or lack of pest
management programs.
Regional differences in some countries may illustrate two fold
yield increases per acre in one-third of the country due to new tech¬
nology yet no change elsewhere within the same country [32, p. 701].
Reasons for thi scondition are in part explained by the Guatemalan
experience. Farmers tend to adopt new technologies as risk is reduced
and when clear i ncome advantages appear. They are not likely to incur
more risk until at least self-sufficiency is established. Thus, risk
reduction can occur within the present self-sufficiency crop and income
patterns and/or in a potential crop addition to that pattern. Both
types of risk reduction may create similar impacts on production systems
changes implemented by traditional farmers.

150
This explanation of traditional farm behavior is corroborated by
Figure 18 where traditional and commercial farm income, total farm
size, and price-quant i ty relationships found in the basic grain supply
response for Guatemala have been depicted. The supply responsiveness
to changes in income, farm size, and price (being larger for traditional
crops than for commercial crops at low income, farm size, and price
levels, but decreasing faster for the former than for the latter at
higher income, farm size, and price levels) has given support to the
conceptual model of this study. In addition, the positions of the
intercepts for the different crops, by being lower for the traditional
than for the commercial crops, further validate the conceptual model.
Because of the different and complementary behavior with both types of
crops, research emphasis must also fall on high risk crops and not just
on basic crops.
In a recent study about rates of adoption of modern inputs in
several developing countries, the authors recognize that "experimenta¬
tion with new techniques involves the risks of the unknown, usually
involving additional investment, and small farmers may be less able to
undertake such risks" [96, p. 888]. This finding is related to the
traditional farmers' behavior, explained in the present study, with
regard to higher risk crops. Even in the case of known varieties,
traditional farmers will not be willing to take any risk until they
have attained individually required self sustaining income levels.
Off-farm and part-time rural employment along with agricultural pro¬
ductivity advances in basic crops can provide this stimulus.

151
Figure ]8.--Trad itiona1 and commercial income, farm size, and
price-quantity relationships in developing
agriculture

152
Second Generation
Second generation problems encompass difficulties associated with
marketing, markets, and resource allocation. Examples of marketing and
demand problems generated by the Green Revolution are: transportation
bottlenecks; differences in milling, grading, storing, and transporting
the products; low consumer acceptance because of quality problems; pricing
and marketing inefficiencies; and, finally, barriers to entering inter¬
national markets.
Falcon [32, p. 701] acknowledges that, even with moderately high
on-farm demand from increased production, quantities marketed have risen
much more than proportionately to quantities produced. In chapter six,
it was recommended that demand studies at the different levels of the
marketing chain be conducted. Most marketing problems can be reduced
with policies and programs based on knowledge of the on-farm elastici¬
ties of demand and the proportion of the increased output the remainder
of the population is willing to absorb at prices commensurate with pro¬
duction costs. On the other hand, if production remains stable while
productivity for a basic grain increases, the market for the basic grain
probably will not receive pressure and falling prices will not result.
To achieve increased productivity, stress may be placed on input market
systems. But possibly more important is the potential pressure on the
market for higher risk commercial crops since farmers may shift to pro¬
ducing these crops after productivity increases have been obtained in
the traditional crops. Risk associated with those commercial crops in

153
part can be reduced by placing emphasis on improving market conditions
and prices for those crops. Furthermore, input market pressure also
may be placed on some non-traditional inputs but not exclusively those
necessary to service traditional basic crops.
Third Generation
Receiving the least attention, third generation problems encompass
equity, welfare, employment, and social institutions. They arise from
four principal sources: First, annual population growth rates of over
2.5 percent in areas already densely populated; second, very low average
income levels, coupled simultaneously with great regional and personal
disparities in income, wealth, and political power; third, limited
opportunities for off-farm employment; and finally, the possibility
for technological "leap-frogging" with agricultural inputs and tech¬
niques, which are often of a labor-displacing nature.
A built-in supply control mechanism for basic grains and low value-
low risk crops produced by the small farm system has been suggested in
the conceptual model. Because of that mechanism, over production, at
least at the small farm level, might not result so prices should not
decline sharply to create great income disparities. On the other hand,
if in order to obtain the desired total production increase at the
national level emphasis is placed on some commercial basic gain produc¬
tion under larger farms, small farmers will be affected by the fall in
basic grain prices.
But if the emphasis is maintained on increased basic grain produc¬
tion by the traditional sector, the government will be enforcing

contradictory policies. That is, a conflict prevails between the pro¬
duction goal, which would not substantially increase average per capita
income of traditional farmers, and the goal of economic development for
the country. Traditional farmers, however, apparently may not be counted
upon to substantially increase total production of basic grains to meet
the national goal. Yet since they do contribute toward that goal, re¬
search on basic grains for traditional farmers is still necessary so
that they can realize the productivity increases that will provide the
opportunity for them to produce higher value crops. If commercial basic
grain prices fall as a result of increased productivity and production,
traditional farmers may be forced back into greater land use for basic
grain production to secure their low risk low money requirements; there¬
fore, research must continue to provide for increases in traditional
basic grain productivity if balanced growth is to occur within the
agricultural sector.
Employment related problems are an integral part of the role of
agriculture in economic development. Today it appears that the need
is not to send rural people to the cities (an old theory to provide
cheap labor) but to employ migrants and potentially displaced small
farmers on farms as a means to reducing unemployment and income dis¬
tribution problems. Rural small industry may serve a double purpose
for the food system by providing needed employment as well as pre¬
processing, processing, packing,and storage for some of the surplus
production. Working part-time off the farm does not imply a decline
in on-farm productive activities. It has been shown in the Guatemalan
situation, that, when husbands take up a part-time job, either in the

155
cities or in the country side, wives remain in charge of agricultural
activities. The added family income and security related thereto may
provide a basis for moving into higher value-higher risk crops just
as traditional crops provide that basis.
Suggestions for Further Research
Having to depend entirely on data collected for a purpose different
than the estimation of the model portrayed in this sutdy has placed some
undeniable limitations on the scope of the research and results. The
most limiting condition has been the impossibility of testing for the
presence of a backward bending supply curve for basic grains. It was
indicated in the conceptual model that, as income and farm size increase
and small farmers move out of subsistence into commercial agriculture,
there is a tendency to cut back on production of traditional crops.
The reciprocal form specified for these variables, due to the nature
of the data, impeded the functions from bending backwards. In the
case of price, the unexpected signs obtained may also signal the pos¬
sibility of a backward sloping supply curve as the result of a limited
surplus available at the end of the season, when prices are high.
Another reason might be the income effect as the farmer moves up and
along the pri ce-income-consumption path to a higher income level. In
the following season, the farmer moves into commercial crop production
and devotes less land to traditional crops. Further research should
test for the possible presence of that supply curve.
For such tests, countries and regions should be carefully selected
to include those with desired yet typical characteristics. Question¬
naires should be designed to collect the necessary and appropriate data,

156
which would of course include sufficient observations of the high-value
and high risk crops. That research, when accomplished, will contribute
to a better understanding of the small farm basic economic system in the
developing nations.
Epilog
Despite the considerable attention given to the modernization of
traditional agriculture during the past quarter century, the small farm
sector has not received sufficent attention. "It is imperative that
this mass of humanity," as pointed out in a recent publication [9^, p.
i], "be included in the modernization process and share in the material
and other benefits of economic development and social progress." The
reasons are fairly simple:
The state of the arts and the knowledge base in
this area are dangerously inadequate. Development
theory treats the problem of this important stratum
of the rural sector inadequately. Much of the empirical
work has abstracted from these problems. Many develop¬
ment projects have failed to achieve desirable impacts
on the rural poor. Information relative to the funda¬
mental characteristics of this stratum and the barriers
which it faces is sparse.
The agricultural development spotlight is now be¬
ginning to focus on the basic issue - the unmitigated
poverty of disenfranchised rural inhabitants. Develop¬
ment efforts have no: alternative but to tackle this
massive problem. To do so effectively will require
sharp expansion of the relevant knowledge base. It
will necessitate modification of conceptual models,
expansion of empirical information and the creation
of effective development strategies and programs.
[91*, P- i]-
That concern has been present throughout this study. Recent de¬
velopments in the literature seem to indicate that the time has already

157
come for proper priority to be given to small farm agricultural de¬
velopment within the general economic development framework. The
results, when incorporated within effective development strategies
and programs, will help resolve one of the most crucial problems
faced by developing countries today.

GLOSSARY1
Aldea: Hamlet or small village.
Associated enterprises: Sequential Intercropping of two or more
crops such that all production practices
refer to the entire combination of the
crops Included.
Cabecera: Capital of a department or munIcipio.
Canton: A territorial subdivision roughly equivalent to a country,
If rural, or a ward, If urban.
Caserío: Rural community too small to be considered an al dea. Often
only a collection of scattered dwellings.
Ciudad: City.
Departamento: Each of the 22 major political subdivisions In which
the Republic is divided.
ICTA: Instituto de Ciencia y Tecnología Agrícolas (institute of
Agricultural Science and Technology). Decentralized Institute
of the Governmental Agricultural Sector Inaugurated on June 1,
1973, with the purpose of conducting research to generate new
technologies mainly for medium and small farmers.
INDECA: Instituto Nacional de Comercialización Agrícola (National
Institute of Agricultural Marketing). A decentralized agency
in charge of all agricultural marketing activities in the
country.
Ladino: According to the 196** Official Census, term applied to anyone
who was not a cultural Indian, which includes persons of
European and Asiatic heritage as well as acculturated Indians.
Manzana: A unit of land equal to 698^.^ square meters.
Milpa: Corn, most of the tIm e Intercropped with beans and/or other
products.
This section Is mostly based on [2¿t]
158

159
Municipio: Political subdivision of a department. Similar to a
township In the United States.
Pueb1 o: V111 age.
Quetzal: Unit of currency, equivalent to one U.S. dollar. Also
the national bird of Guatemala.
Quintal: A unit of weight equal to 100 pounds, or ^5>359 kilos.
Villa: Small town, larger than a pueblo.

APPENDIX

APPENDIX
The primary purpose of this study has been the estimation of
market supply functions for basic grains in the different regions
of Guatemala. This appendix contains the list of crops involved,
a complete specification of the mathematical and statistical models,
and the regression results.
List of Crops
Basic grains include corn, beans, sorghum, rice, and wheat.
They may be grown as single crops or associated with one or more
crops. The regional distribution of crops for which equations are
estimated is as follows: For the associations, corn-beans (C-B) in
Rj, Rr, and R^; corn-sorghum (C-S) in R^; and corn-beans-sorghum
(C-B-S) in R^; corn in R^, R^, R^, R,., and R^; beans (B) in R^ ,
R^, and R^; sorghum (S) in R^ only; rice (R) in R^, R,., and R^; and,
finally, wheat (W) in R. and R¿.
I b
The Mathematical Model
The theoretical model developed in chapter three provides the
basis for the estimation of the surplus-output ration as a function
of a number of independent variables. Variables in the equation are
161

162
M T
Q. / Q. = quantity marketed divided by quantity produced of
basic grain i; or percent of basic grain i that
is marketed (the dependent variable);
P. = farm price of basic grain i (quetzales/kg);
E. = education of household head (number of year of
formal education):
A. = total farm size (ha);
D. = distance to the nearest market (km);
I. = quantity of basic grain i demanded at the farm level
for all purposes (kg);
W. = return per hectare in all basic grains except basic
grain i divided by return per hectare in basic grain
i (quetza1es/kg/ha); and
Y. = total annual family income (quetzales).
Descriptive statistics for each of the independent variables appear
in Taole A-l to Table A~7. Their implications have been discussed in
chapter six.
Before stating the mathematical form of the behavioral equation to
be estimated, some assumptions regarding the behavior pattern of the in¬
dependent variables must be made. It is assumed that education (E.),
distance (D.), quantity demanded on the farm (I.), and the relative
profitability ratio (W.) enter the equation in direct form. It is
further assumed that, based on the conceptual model, price (P.), total
family income (Y.), and total farm size (A.) enter the equation in
reciprocal form. Since quantity marketed (Q.) is the only endogenous
variable, the model can be solved with the following single equation:

Table A-1.--The price variable: descriptive statistics for each of the estimated equations
Region
Crop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtosis
Skewness
1
C-B
0.085
0.235
0
63
0.131
0.027
3.57
1.66
5
C-B
0.072
0.306
0
33
0.150
0.042
4.92
1.76
6
C-B
0.115
0.271
0
45
0.194
0.040
-0.57
-0.08
6
c-s
0.055
0.176
0
38
0.110
0.018
5.69
0.01
6
C-B-S
0.105
0.236
0
16
0.154
0.034
-0.17
0.73
1
C
0.052
0.213
0
86
0.126
0.026
1.75
0.14
3
C
0.012
0.147
0
51
0.103
0.024
4.62
-1.83
4
C
0.041
0.170
0
208
0.111
0.020
1.36
-0.56
5
C
0.028
0.382
0
250
0.114
0.034
17.70
2.72
6
C
0.054
0.265
0
141
0.116
0.027
8.36
2.04
1
B
0.116
0.711
0
21
0.308
0.114
5.99
2.00
5
B
0.037
0.491
0
63
0.280
0.089
-0.07
-0.08
6
B
0.110
0.750
0
124
0.291
0.091
5.68
1 .26
4
S
0.066
0.221
0
42
0.112
0.028
9.19
2.71
4
R
0.077
0.419
0
52
0.190
0.084
0.59
1 .18
5
R
0.023
0.287
0
50
0.120
0.048
3.51
1.13
6
R
0.110
0.386
0
28
0.217
0.066
0.05
0.47
1
W
0.095
0.282
0
204
0.169
0.026
2.39
-0.13
6
W
0.129
0.185
0
25
0.167
0.022
-0.94
-1 .01

Table A-2.--The education variable: descriptive statistics for each of the estimated equations
Region
Crop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtes i s
Skewness
1
C-B
1
6
42
63
3.33
1.80
-1.07
0.46
5
C-B
1
6
15
33
2.94
1.31
-0.03
0.80
6
C-B
1
9
19
45
3.62
2.04
-0.00
0.74
6
c-s
2
6
23
38
3.53
1.41
-0.79
0.61
6
C-B-S
2
6
7
16
3.67
1.66
-1.20
0.44
1
C
1
9
30
86
3.46
1.68
0.62
0.90
3
C
1
6
18
51
3.12
1.64
-0.64
0.43
4
C
1
7
106
208
2.92
1.36
0.71
0.97
5
C
1
18
106
250
4.16
3.02
6.43
2.32
6
c
1
11
63
141
3.36
1.82
2.48
1.39
1
B
1
6
6
21
2.80
1.57
0.33
0.98
3
B
2
6
24
63
3.46
1.45
-0.75
0.70
6
B
1
11
57
124
3-34
1.80
3.41
1.63
4
S
1
6
20
42
2.91
1.15
1.27
0.79
4
R
1
6
30
52
2.86
1.64
-0.30
0.79
5
R
1
18
32
50
6.00
4.86
2.09
1.72
6
R
2
6
14
28
4.36
1.65
-1.55
-0.18
1
W
1
18
79
204
3.40
2.38
15.39
3.39
6
W
2
6
15
25
3.20
1.32
0.57
1.29

Table A-3.-_The total farm size variable: descriptive statistics for each of the estimated equations
Region
Crop
Min.
Max
Missing
Observ.
N
Mean
St.
Dev.
Kurtosis
Skewness
1
C-B
0.70
41 .90
0
63
8.89
10.08
2.96
1.96
5
C-B
1 .20
59.39
0
33
7.25
10.85
15.00
3.77
6
C-B
1 .40
55.90
0
45
8.75
10.67
7.23
2.58
6
c-s
1 .40
103.41
0
38
18.19
22.87
5.78
2.43
6
C-B-S
1 .40
55.90
0
16
14.30
15.22
1.61
1.46
1
C
0.44
29.07
0
86
4.90
5.39
8.32
2.80
3
C
1.40
87.34
0
51
16.22
19.42
6.57
2.62
4
C
0.92
67.08
0
208
1 1 ; 22
10.43
5.85
2.07
5
C
0.70
449.99
0
250
17.13
48.21
52.91
6.93
6
C
0.70
238.27
0
141
12.64
25.50
43.41
5.76
1
B
0.70
10.84
0
21
3.93
2.48
1.12
1 .05
5
B
0.09
405.03
0
63
24.34
68.16
24.46
5.06
6
B
0.70
238.27
0
124
15.96
29.31
26.63
4.45
4
S
0.70
69.87
0
42
14.61
15.32
3.62
1 .98
4
R
0.70
55.20
0
52
14.43
11.71
2.87
1 .60
5
R
2.23
89.44
0
50
16.62
17.96
8.85
2.91
6
R
2.79
55.90
0
28
13.82
14.14
3.12
1 .96
1
W
0.22
44.72
0
204
4.42
5.55
17.54
3.68
6
W
2.52
23-06
0
25
6.44
4.89
4.44
2.17

Table A-4.--The distance to market variable: descriptive statistics for each of the estimated equations
Region
Crop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtosis
Skewness
1
C-B
1
92
4
63
12.73
14.77
19.55
4.36
5
C-B
1
40
0
33
26.85
11.16
0.35
-1.28
6
C-B
1
54
4
45
7.71
9.04
15.72
3.76
6
c-s
1
30
2
38
10.25
8.14
0.45
1.22
6
C-B-S
2
26
2
16
8.57
6.81
1.98
1 .76
1
C
1
150
20
86
14.12
25.99
13.59
3.66
3
c
1
76
4
51
22.36
21 .66
-0.41
0.94
4
c
1
137
20
208
21 .38
20.71
6.19
2.10
5
c
1
120
21
250
10.34
12.83
32.20
4.68
6
c
1
55
16
141
11.06
10.74
4.40
2.05
1
B
1
110
2
21
21.32
26.08
5.60
2.41
5
B
1
40
10
63
11.06
9.34
1.41
1.44
6
B
1
163
13
124
14.20
18.92
33.46
4.91
4
S
1
70
4
42
18.40
22.18
0.70
1.51
4
R
1
137
7
52
24.13
23.76
9.61
2.53
5
R
1
100
5
50
15.00
17.68
10.33
2.82
6
R
1
12
6
28
5.5
3-13
-0.72
0.42
1
W
1
150
20
204
12.78
20.16
16.75
3.79
6
W
1
23
0
25
8.60
6.90
-0.77
0.71

Table A-5.
--The quantity demanded on the farm variable: descriptive
equations
statistics
for each of the estimated
Region
C rop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtosis
Skewness
1
C-B
296
7712
0
63
2332
1309
5.50
1.88
5
C-B
158
9753
0
33
1355
1824
13.23
3.67
6
C-B
45
5895
0
45
1857
1176
2.23
1.14
6
C-S
454
7712
1
38
2697
1799
1 .43
1 .48
6
C-B-S
1020
6734
0
16
2745
1665
0.45
1.14
1
C
23
5443
0
86
1382
955
4.52
1 .87
3
C
363
7712
1
51
2371
1595
2.05
1 .42
4
C
272
8165
6
208
1804
1181
6.75
2.08
5
C
45
12701
20
250
1293
1242
36.28
4.78
6
C
91
30074
3
141
1717
3060
54.65
6.74
1
B
25
2722
1
21
356
633
8.74
3.14
5
B
23
1134
1
63
187
194
8.35
2.58
6
B
90
3765
10
124
419
455
27.75
4.66
4
S
45
1814
19
42
471
409
3.22
1.67
4
R
45
1361
14
52
239
233
12.61
3.28
5
R
45
2722
19
50
433
680
6.32
2.73
6
R
45
11567
2
28
907
2238
19.28
4.57
1
W
11
3720
51
204
420
537
16.33
3.65
6
W
136
499
0
25
317
256
-1.00
0.00

Table A-6.--The relative profitability ratio variable: descriptive statistics for each of the
estimated equations
Region
Crop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtos i s
Skewness
1
C-B
0.013
3.51
52
63
1.45
1.14
-0.77
0.52
6
C-B
0.005
1.38
34
45
0.23
0.39
6.06
2.86
6
c-s
0.013
6.09
14
38
0.76
1.43
7.33
2.86
6
C-B-S
0.019
1.95
11
16
0.45
0.84
1.00
1.83
1
C
0.112
9.77
33
86
1.51
1.71
10.16
2.91
3
C
1.293
5.64
47
51
2.75
2.01
-0.20
1 .21
4
C
0.039
79.65
138
208
3.89
13.30
28.41
5.47
5
C
0.005
16.88
168
250
1.16
2.36
27.28
4.97
6
C
-1.143
12.55
46
141
1.41
2.22
11.62
3.24
1
B
0.129
27.54
8
21
3.73
7.84
5.45
2.67
5
B
0.013
6.06
13
63
0.59
0.99
18.52
4.07
6
B
0.007
4.64
31
124
0.49
0.71
12.40
3.07
4
S
0.102
76.18
2
42
4.89
12.38
26.91
5.20
4
R
0.003
2.30
7
52
0.51
0.54
2.40
1 .61
5
R
0.006
5.62
11
50
0.57
1.02
14.25
3.65
6
R
0.022
2.51
0
28
0.37
0.50
11.15
3-34
1
W
-5.450
4.03
141
204
0.32
0.97
26.51
-2.90
6
W
0.036
0.52
10
25
0.26
0.16
-1 -27
0.13

Table A-7---The total income variable: descriptive statistics for each of the estimated equations
Region
Crop
Min.
Max.
Missing
Observ.
N
Mean
St.
Dev.
Kurtosis
Skewness
1
C-B
107
3960
0
63
908
839
3.76
2.04
5
C-B
180
7765
0
33
1445
1697
4.83
2.27
6
C-B
158
13128
0
45
2095
2643
9.63
3.12
6
C-S
158
8526
0
38
1593
1695
7.50
2.71
6
C-B-S
158
4250
0
16
1371
1066
1.60
1 .32
1
C
35
7891
0
86
1009
1233
11.03
2.95
3
C
150
18685
0
51
2049
3555
16.99
4.22
4
C
93
36323
0
208
2745
3703
32.93
4.58
5
C
41
47600
0
250
2033
4650
72.69
7-96
6
C
60
29025
0
141
1664
3665
33.72
5.47
1
B
33
2807
0
21
659
663
4.14
2.20
5
B
53
5467
0
63
1341
1352
1.58
1.48
6
B
60
29025
0
124
1880
3883
29.11
5.09
4
S
197
36323
0
42
3253
5691
26.36
5.04
4
R
146
12040
0
52
2968
2806
1 .30
1.37
5
R
140
47600
0
50
3729
9626
15-50
4.07
6
R
383
14385
0
28
3333
4082
1.66
1 -75
1
W
8
7891
0
204
665
893
24.49
4.26
6
W
110
3663
0 !
25
710
669
14.17
3.71

170
Q1? / qT = Bo - B. 1 + B0 E. - B, 1 + B, D. - Bn I. + B, W.
i i Ip. 2 i 3 ^ 4 . 5 i 6 .
i ¡
Y.
Setting the direct variables equal to their means, the following expres¬
sion is obtained:
M T
Q. / Q. = Z - Bi, where X is one of the three variables (Y., A., P.)
1 1 X ill
estimated in reciprocal form and Z is the intercept value with all vari¬
ables other than X at their means.
M T
From the theoretical presentation, Q. / Q. should steadily approach
nearer and nearer to the value one, without ever attaining this value.
The magnitude of the response depends on the traditional or commercial
character of the crop. In terms of limits,
1 im / qT = 1 im (Z - 3j_)
1 ' X
x-*» . .
= Z - 1 im
x
x-**>
=Z
where 0 < Z _< 1 .0.
The mathematical properties of the function can be illustrated with
the following computations. Let us assume, for simplicity, that
Y = 1 - a .
X
Then, when a = 1, and X takes on values of 1, 10, 100, ... , Y equals
0, 0.9, 0.99, ••• ', and when a = 10, and X takes on values of 10, 100,
1,000, ... , Y equals 0, 0.9, 0.99•••(Figure A-l). Each function*
approaches the value one with a different slope depending on the value
of X, while their intercepts depend on the value of a.

171
Figure A-l.--Mathematical properties of the specified
function

172
The Statistical Model:
Its Assumptions and Possible Violations
The specification of the linear regression model includes the
regression equation and the basic assumptions. This section contains
the full specification of the model and discusses possible violations
of the basic assumptions.
The Regression Model
The multiple regression model is formally described as
R
Y. = a +.E. RX. + e . ,
i i=l 1 i
where Y is called the "dependent variable", X the "independent (or
explanatory) variables", e the "stochastic disturbance", a and Rthe
unknown "regression parameters", and the subscript i refers to the
ith observation [65, p. 201].
The basic assumptions of the cross-section model are:
(a) Normality: e. is normally distributed,
(b) Zero mean: E(e.) = 0,
2 2
(c) Homoskedasticity: E(e.) = a ,
(d) The number of observations exceeds the number of coefficients
to be estimated, and
(e) No exact linear relation exists between any of the explanatory
variables [65, p. 202, 3^8].

173
Possible Violations of the Assumptions
The main purpose of the model is to estimate the regression para¬
meters by means of the assumptions underlying the model. It may be
possible, however, that, in so doing, one or more of the basic assump¬
tions may not be fulfilled. The purpose of this section is to explore
the possibility that this condition has in fact occurred in this study.
All assumptions are scrutinized to show that the least squares estima¬
tors of the regression parameters have all of the desirable properties.
Normality.--When the assumption of normality is not fulfilled, the
least squares estimators of the regression coefficients are still the
best linear unbiased estimators (BLUE), since this property is inde¬
pendent of the form of the parent population. They are therefore still
unbiased and have the smal 1 est variance among all linear unbiased esti¬
mators of the respective parameters. Though they are no longer effi¬
cient, they can be considered consistent and asymptotically efficient.
One practical implication of dropping the normality assumption is
that the confidence intervals and tests performed no longer apply.
However, they are not too badly affected and can be used as reasonable
approximations, when the disturbance's distribution is not very radically
different from normal [65, pp. 247“8].'
Validity of the normality assumption in the statistical model was
evaluated through a direct examination of the residuals. All plots
examined were found to have a pattern resembling very closely that of
a normal distribution.

174
Zero mean.--The zero mean assumption of the regression disturbance
is based on the specification that the population regression line is
E(Y.) = a + E0X .
If the mean of the disturbance values is, for example, p. , instead of
zero, then
E(Y.) = a + Z3X. + p.
When p. is a constant, E(Y.) = a*+ IBX., and the least squares formula
gives an estimation of a*instead of a, though the least squares estima¬
tion of B's are unaffected. There exists no possibility in this case
for est¡matinga and pseparate 1y and for obtaining unbiased or at least
consistant estimates. When p. varies from observation to observation,
a becomes (a+ p.); thus, the dependent variable changes for both changes
in the X.'s and for other reasons [65, pp. 248-9}.'1-
The above situation may be the result of specification error due
to the exclusion of some relevant explanatory variables from the equation.
An examination of the behavior of the regression residuals can be used to
test for this specification error [65, p. 405]. In this case, the
scrutiny of residuals in all the equations provides no reason to believe
that the zero mean assumption of the model has been violated.
Homoskedasticity.--The characteristic of the regression disturbance
known as homoskedasticity implies a constant variance of the disturbance
for all observations. When this does not hold, then
a 2\ 2
E(e.) = 0. ,
which implies that the variance of the disturbance may vary from obser¬
vation to observation. The least squares estimators, though still unbiased,

175
cease to be BLUE, and, therefore, do not have the smallest variance in
a class of unbiased estimators and are not efficient. They are still
consistent but have lost the property of being asymptotically effi¬
cient. When heteroskedasticity is present, confidence intervals and
tests of hypotheses are meaningless [65, pp. 249-56’; 59] -
Although the composition of the sample is such that variation
among the variances of the disturbance is very unlikely, a test was
conducted to corroborate that assertion. Total family income and total
farm size are the only two variables with a possibility of violating the
homoskedasticity assumption. When the disturbance was plotted against
these two variables for each of the estimated equations, there appeared
no reason to believe that this assumption would not hold in every equation.
Sufficient observations.--This assumption requires that the number
of observations exceed the number of coefficients to be estimated, thus
fulfilling the provision for a sufficient number of "degrees of freedom"
in estimation. In all equations this assumption is satisfied; the number
of observations always exceed the number of parameters.
No mu 11i col 1inearity.--No exact linear relationship should exist
between any of the explanatory variables. When this assumption does not
hold, perfect mu 11 i col 1 i near i ty is present.: However, muí t i col 1 i near i ty
is a question of degree and, therefore, we do not test for multicol-
linearity but measure its degree in any particular sample.
Perfect muíti col 1inearity causes the (X* X) matrix in the least-
squares estimatorB= (X X) X Y to be singular. In the case of high
but not perfect muíti col 1 inearity, it becomes very difficult to disen¬
tangle the separate effects on the dependent variable of the independent

176
variables. The result is the presence of large standard errors of the
regression coefficients and the consequent widening of the acceptance
region for the hypothesis that a given coefficient is zero. In turn,
the possibility of making mistakes in accepting or rejecting hypotheses
is very plausible.
The no-multi col 1inearity assumption was tested by closely examining
the matrices of simple correlation coefficients of the independent vari¬
ables (Table A-8 to Table A-26). Only in 10 cases, out of a possible
399, do the variable combinations show a simple correlation coefficient
larger than .50, but, in half the cases, these values are very close to
• 50. Those occur with total income and farm size (.51) ir. the corn
equation for R^ (Table A-lA) and for R^ (Table A-15)- A value of .53
is observed between distance and farm size in the R^ wheat equation
(Table A-26), total income and farm.size;; in the R^ corn-bean equation
(Table A-10), and between distance and price in the R^ corn-bean-sorghum
equation (Table A-12). Price and farm, size in the wheat equation of
R^ show a value of .59 (Table A-26).
Larger values appear in a few instances. Price and distance pre¬
sent a value of .69 in the R^ wheat equation (Table A-26). Total income
and price show a .62 in the R^ sorghum equation (Table A-21), total
income and farm size., of .81 in the R^ corn-sorghum equation (Table A-1 1) ,
and .8A in the R^ corn-beans-sorghum equation (Table A-12).
Considering the small number of cases where variable combinations
present a simple correlation coefficient larger than .50, and the speci¬
fic circumstances when they occur, it is safe to infer that multicol-
linearity is not distorting the 1east-squares-estimates in any of the
equations.

177
Regression Results
Results obtained from estimating the equations are presented in
Table A-27. Numerical values computed for depicting the income, total
farm size, and price-quantity relationships are also shown (Table A-28
to Table A-37).

178
Table A-8.
--Rj corn-beans:
the independent
simple correlation
variables
coefficients
matrix of
P.
i
E. A.
i i
D. 1 .
i i
W.
i
Y.
i
P.
i
1.00 -0.06
-0.29
0.08
0.09
0.22
-0.29
E.
i
1.00
0.04
-0.28
0.04
0.03
-0.06
A.
i
1 .00
-0.24
-0.39
-0.09
0.34
D.
i
1 .00
0.17
0.07
-0.25
1 .
i
1 .00
0.18
-0.34
W
i
1 .00
0.02
Y
i
1 .00
Table A—9• —Rj- corn-beans: simple correlation coefficients matrix of
tne independent variables
P.
i
E.
i
A.
i
D.
i
1 .
i
w.
1
Y.
1
P.
i
1 .00
-0.08
0.02
-0.01
-0.16
0.00
0.11
E.
i
1 .00
-0.16
-0.03
-0.34
0.00
-0.37
A.
i
1 .00
-0.02
-0.42
0.00
0.37
D.
i
1 .00
0.13
0.00
-0.17
1 .
i
1 .00
0.00
-0-34
W.
i
1 .00
0.00
Y.
1 .00

179
Table
A-10.
"'tí
corn-beans:
íe independent
simple correlation
variables
coefficients matrix of
P.
i
E. A.
i i
D.
i
1 .
i
W.
i
Y.
i
P.
i
1 .00
0.33 0.21
-0.12
-0.23
-0.0*4
0. *42
E.
i
1.00 0.01
0.13
-0.15
-0.15
-0.0*4
A.
i
1 .00
0.22
-0.2*4
0.26
0.53
D.
i
1 .00
-0.10
0.16
-0.02
1 .
i
1 .00
0.16
-0.21
W.
i
1 .00
-0.08
Y.
i
1 .00
Table
A-11 .
"tí
corn-sorghum
íe independent
simple
variables
correlation coefficients matrix of
P.
i
E. A.
i i
D.
i
1 .
i
W.
i
Y.
i
P.
i
1.00 -0.05
-0.03
-0.32
-0.06
-0.2*4
0.0*4
E.
i
1 .00
-0.08
-0.35
-0.02
0.31
-0.07
A.
i
1 .00
0.13
-0.*4l
0.13
0.81
D.
i
1 .00
0.02
-0.06
-0.06
1 .
i
1 .00
0.01
-0.*40
W.
i
1 .00
0.22
Y.
1 .00

i so
Table A-12.-~Rg corn-beans-sorghum: simple corrleation coefficients
matrix of the independent variables
p.
1
LLi
A.
i
D.
i
1 .
i
w.
i
Y.
i
P.
i
1.00 0.22
0.47
-0.53
-0.17
-0.08
0.41
E.
i
1 .00
-0.12
-0. -47
-0.04
-0.16
-0.05
A.
i
1 .00
0.07
-0.45
0.36
0.84
D.
i
1 .00
0.19
0.34
0.10
1 .
i
1 .00
-0.04
-0.38
W.
i
1.00
0.34
Y.
i
1 .00
Table A-13-““Rj corn: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
i
D.
i
1 .
i
W.
1
Y.
i
P.
i
1 .00
-0.03
-0.05
0.36
0.01
-0.04
0.45
E.
i
1 .00
0.00
-0.05
-0.11
0.16
-0.08
A.
i
1 .00
-0.14
-0.29
0.1 1
0.33
D.
i
1.00
0.08
0.02
-0.12
1 .
i
1 .00
0.01
-0.24
W.
i
1 .00
0.06
Y.
i
1 .00

181
Table A-14.-
-R corn: simple correlation coefficients matrix of
independent variables
the
p.
E.
i
A.
i
D. 1
i
W.
i i
Y.
P.
i
1.00 -0.03
-0.18
0.38
0.08
-0.03
-0.11
E.
i
1.00
-0.10
-0.23
0.08
-0.04
0.10
A.
i
1 .00
-0.22
-0.31
0.16
0.51
D.
i
1 .00
-0.10
-0.11
-0.19
1 .
i
1 .00
0.06
-0.16
W.
i
1 .00
0.06
Y.
i
1 .00
Table A-15.__R¿} corn: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
1
D.
1 .
i
w.
1
Y
p.
1
1 .00
-0.04
-0.09
0.11
0.08
-0.16
-0.03
E.
1
1.00
-0.05
-0.02
-0.04
0.07
-0.10
A.
i
1 .00
-0.27
-0.30
0.03
0.51
D.
i
1 .00
0.16
-0.01
-0.11
1 .
i
1 .00
-0.01
-0.18
W.
i
1 .00
0.06
Y.
i
1 .00

182
Table A-16.—R corn: simple correlation coefficiencts matrix of the
independent variables
p.
1
E.
i
A.
i
D.
i
1 .
i
W.
i
Y.
i
P.
i
' 1.00 -0.06
-0.21
0.16
0.14
-0.05
0.06
E.
i
1.00
-0.10
-0.01
-0.13
-0.04
-0.11
A.
i
1 .00
-0.09
-0.24
0. 11
0.13
D.
i
1 .00
0.09
0.11
-0.08
1 .
i
1 .00
-0.04
-0.05
W.
i
1 .00
-0.03
Y.
i
1 .00
Table A—17-—R^ corn: simple correlation coefficients matrix of the
independent '- variables
P.
i
E.
i
A.
i
D.
i
1.
1
w.
1
Y.
i
p.
1
1 .00
-0.01
0.05
0.08
-0.09
0.02
0.19
E.
1
1.00
-0.25
0.17
0.03
-0.06
-0.14
A.
1
1 .00
-0.10
-0.26
0.11
0.39
D.
i
1 .00
-0.03
-0.15
-0.06
1 .
i
1 .00
0.00
-0.26
w.
1
1 .00
0.09
Y.
i
1 .00

183
Table A—18.— R^ beans: simple correlation coefficients matrix of the
independent variables
p.
1
E.
i
A.
i
D. 1
i
W.
i i
Y.
i
P.
i
1.00 -0.44
-0.36
-0.21
0.11
0.19
-0.14
E.
i
1 .00
0.22
0.07
0.17
-0.08
0.05
A.
i
1 .00
0.14
-0.26
0.10
-0.09
D.
i
1 .00
-0.04
0.04
-0.10
1 .
i
1 .00
0.20
-0.14
W.
i
1 .00
0.18
Y.
i
1 .00
Table A— 19.—Rj. beans: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
i
D.
i
1 .
i
w.
1
Y.
1
p.
1
1 .00
-0.01
0.03
0.02
-0.06
-0.03
-0.05
E.
i
1 .00
0.41
0.02
0.01
-0.15
0.03
A.
i
1 .00
-0.03
-0.16
0.03
0.07
D.
i
1 .00
0.10
0.03
-0.29
1 .
i
1 .00
-0.02
-0.38
W.
i
1 .00
0.14
Y.
i
1 .00

184
Table A-20.--R^ beans: simple correlation coefficients matrix of the
independent variables
CL
E.
i
A.
i
D.
i
1 . W.
i i
Y.
i
P.
i
1.00 -0.09
0.05
-0.01
-0.09
-0.09
0.20
E.
i
1 .00
-0.17
-0.01
-0.06
-0.11
-0.05
A.
i
1 .00
0.00
-0.30
-0.0b
0.31
D.
i
1 .00
-0.06
-0.02
-0.03
1 .
i
1 .00
-0.05
-0.23
W.
i
1 .00
-0.03
Y.
i
1 .00
Table A-21.--R^ sorghum: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
i
D.
i
1 .
i
W.
i
Y.
i
P.
i
1 .00
-0.01
-0.07
-0.0b
0.1 1
0.07
0.62
E.
i
1 .00
0.05
-0.02
-0.08
0.17
0.06
A.
i
1 .00
-0.24
-0.25
0.07
0.22
D.
i
1 .00
-0.13
0.26
-0.21
1 .
i
1.00
-0.02
-0.07
W.
i
1 .00
0.23
Y.
i
1 .00

135
Table A-22.--R^ rice: simple correlation coefficients matrix of the
independent variables
p.
1
E.
i
A.
i
D.
i
1 . W.
i i
Y.
i
P.
i
1.00 -0.14
-0.03
0.11
-0.04
0.01
0.23
E.
i
1 .00
-0.23
0.30
0.03
0.03
-0.03
A.
i
1 .00
-0.11
-0.28
0.01
0.26
D.
i
1 .00
-0.27
0.13
-0.03
1 .
i
1 .00
0.14
-0.34
W.
i
1 .00
-0.18
Y.
i
1 .00
Table A-23-—Rj- rice: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
i
D.
i
1.
1
w.
1
Y.
i
P.
1
1 .00
-0.28
-0.08
-0.04
-0.17
CNI
CM
O
1
0.37
E.
i
1 .00
-0.19
-0.08
0.01
-0.01
-0.31
A.
i
1 .00
0.10
-0.24
-0.30
0.15
D.
i
1 .00
-0.09
0.12
-0.20
1 .
i
1 .00
0.11
-0.23
W.
i
1 .00
0.04
Y.
i
1 .00

186
Table A-24.--R^ rice: simple correlation coefficients matrix of the
independent variables
p.
1
E.
i
A.
i
D.
i
1 .
i
W.
i
Y.
i
P.
i
1 .00
0.10
-0.30
-0.25
o.kk
-0.17
-0.20
E.
i
1 .00
-0.03
-0.39
-0.03
0.02
-0.A1
A.
i
1 .00
0.27
-0.33
-0.12
0.32
D.
i
1 .00
-0.01
-0.01
0.15
1 .
i
1 .00
-0.05
-0.33
W.
i
1 .00
-0.01
Y.
i
1 .00
Table A-25-_-Rj wheat: simple correlation coefficients matrix of the
independent variables
P.
i
E.
i
A.
i
D.
i
1.
1
W.
i
Y.
i
P.
i
1 .00
-0.1 1
-0.15
0.00
-0.04
-0.17
-0.08
E.
i
1.00
-0.02
0.01
0.22
0.03
-0.11
A.
i
1.00
-0.14
-0.23
0.11
0.19
D.
i
1 .00
0.10
-0.01
0.09
1 .
i
1 .00
-0.11
-0.11
W.
i
1 .00
0.05
Y.
i
1 .00

187
Table A-26.--R^ wheat: simple correlation coefficients matrix of the
independent variables
p.
1
LÜ
A.
i
D.
i
1 .
i
w.
i
Y.
i
P.
i
1 .00
0.05
0.59
0.69
-0.02
-0.50
0.17
E.
i
1.00
-0.16
0.09
-0.00
-0.33
-0.32
A.
i
1.00
0.53
-0.04
-0.40
0.42
D.
i
1.00
-0.02
-0.39
0.05
1 .
i
1 .00
0.05
-0.06
W.
i
1 .00
0.19
Y.
1.00

Table A-27-—Regression coefficients for each basic grain or association by
regions of Guatemala
a
Region
Crop
Constant
P.
1
E. A.
i 1
D. 1 .
1 1
W. Y.
1 1
d!f.
R2
1
C-5
0.27392
-0.00524f
(0.00419)
0.00482f -0.08943b
(0.00541) (0.01974)
0.00024 -0.00001b
(0.00040) (0)
0.00144d -10.61613b
(0.00099) (4.25824)
55
.33
5
C-B
0.28718
-0.004159
(0.00500)
0.00364 -0.05829f
(0.01175) (0.05218)
0.00126d-0.00001f
(0.00093)(0.00001)
0 - 6.04527
(0) (9.61876)
26
.02
6
C-B
0.34978
-O.OO388
(0.00642)
0.006A7d -0.08l92d
(0.00481) (0.05403)
0.00049 -0.00003b
(0.00082) (0.00001)
-0.00412 -I6.55984b
(0.00753) (7.64936)
37
.44
6
c-s
0.19378
-0.00112
(0.00267)
0.005409 -O.052I7f
(0.00665) (0.05855)
-0.00074f-0.00001b
(0.00076) (0)
0.01l47b - 7•57932f
(0.00428) (7.34657)
30
• 34
6
C-B-S
0.51144
-0.010839
(0.01299)
0.00509 -0.36586°
(0.01283) (0.14030)
-0.00335f-0.00002°
(0.00326)(0.00001)
-0.02748 20.90172d
,(0.05376) (14.82739)
8
.50
1
C
0.44802
0.0288413
(0.01312)
0.01116 -0.14456°
(0.01686) (0.07254)
0.0017 6d-0.0001lb
(0.00113)(0.00003)
0.00129f -20.41058b
(0.00148) (7.41719)
78
.28
3
c
1.03937
-0.00049
(0.00162)
0.00699 -0.37019b
(0.01321) (0.13443)
0.00019 -0.00006b
(0.00092)(0.00001)
-0.00528b-l05.81248b
(0.01877) (16.74541)
43
.70
4
c
1.01518
-O.OOI93
(0.00502)
-0.00305 -0.20645b
(0.01266) (0.07638)
0.00035 -0.00007b
(0.00063)(0.00001)
O.Ol868b- 75•78100b
(0.00524) (8.82157)
200
.44
5
c
0.76560
0.00881b
(0.00380)
0.01286b -0.08178°
(0.00528) (0.04451)
-0.00129d-0.00008b
(0.00099)(0.00001)
-0.00029 - 39.90728b
(0.00126) (4.50239)
24*2
.38
6
c
0.46929
0.02270b
(0.00897)
0.01256f -0.00962
(0.01301) (0.07740)
-0.00052 -o.ooooif
(0.00171)(0.00001)
0.00352°- 32.85251b
(0.00178) (9.40590)
133
.12
1
B
0.33231
0.07544b
(0.02915)
-0.020719 0.31937b
(0.02981) (0.11896)
0.00010 -0.00004
(0.00139)(0.00006)
-O.OOO7I - I6.94399b
(0.00367) (5.60921)
13
.43
5
8
0.76875
0.005329
(0.00665)
0.00880 -0.02692°
(0.02105) (0.01234)
-0.00188S-0.00013f
(0.00261)(0.00012)
0.00014 - 11.58go8d
(0.00151) (8.50285)
55
.01

Table A-27.--continued
Region
Crop
Cons tant
P,
1
E.
1
A.
1
D. 1 ,
1 t
W. Y.
1 t
d.f.
R2
6
B
0.63009
0.0366315
(0.01099)
0.01075f
(0.01149)
0.09483d
(0.06430)
0.00046 -0.00020b
(0.00082)(0.00003)
-0.00067k -32.08327k
(0.00026) (7.43973)
116
.34
It
S
1 .01(221
0.00095
(0.00953)
-0.01663^
(0.01608)
0.03633
(0.06260)
0.00087f-0.00015k
(0.00C69) (0.00004)
0.00307k -27.06131d
(0.00320) (16.50459)
34
.40
It
R â– 
0.94006
0.00730b
(0.00238)
0.00957C
(0.00542)
0.01260
(0.02230)
-0.'00049c-0.00012b
(0.00027)(0.00003)
0.00669k - 7.14182d
(0.00147) ( 5.18718)
44
.45
5
R
0.98878
0.000639
(0.00090)
0.00077
(0.00227)
-0.12806d
(0.07980)
0.00017 -0.00004k
(0.00037) (0.00001)
-O.OOO32 -10.63218b
(0.00218) (4.37460)
42
.23
6
R
0.88339
-O.OO58I
(0.01153)
0.016 30 f
(0.01713)
-0.02060
(0.19699)
0.005209-0.00004b
(0.00678)(0.00001)
0.001729 -76.41856c
(0.00223) (31.31350)
20
.46
1
W
0.92030
-0.00893f
(0.00871)
0.01989k
(0.00509)
-0.03073C
(0.01631)
0.00019 -0.00020b
(0.00049)(0.00002)
0.01076c - 3-37986b
(0.00648) (0.96901)
196
.37
6
W
1.02771
-0.00331d
(0.00225)
-0.00206f
(0.00183)
-0.02066f
(0.01798)
-0.00012 -0.00031b
(0.00028)(0.00001)
-0.01455° 0.01958
(0.00580) (0.92662)
17
.96
aFigures in parentheses are standard errors. C, B, S, R, and W represent corn, beans, sorghum, rice, and wheat,
respect ively.
^Significant at the 99 percent level.
CSignificant at the 95 percent level.
Significant at the 90 percent level.
Significant at the 80 percent level.
Significant at the 60 percent level.
Significant at the 50 percent level.

Table A-28. — Income-quantity relationships for the associations graphed in Figure 8a
Y.b
1
C-B
C-B
C-B
C-S
1
5
6
6
a"
aT
qh
qt
qh
qt
qh
<¡T
10
77^0
9672
5564
6920
2102
3959
11951
14578
20
1 1 302
13534
7600
8956
3942
5849
16442
19069
50
15565
17797
9492
10848
6340
8197
20763
23390
100
17653
19885
10323
11679
7605
9462
22676
25303
200
18892
21124
10787
12143
8397
10254
23754
26381
bOO
19572
21804
11034
12390
8845
10702
24329
26956
600
19808
22040
11118
12474
9003
10860
24526
27153
800
19928
22160
11161
12517
9083
10940
24626
27253
1000
20001
22233
11187
12543
9133
10990
24686
27313
1200
20049
22281
11204
12560
9165
1 1022
24726
27353
i4oo
20084
22316
11216
12572
9189
11046
24755
27382
1600
20111
22343
11225
12581
9207
11064
24777
27404
1800
201 31
22363
11233
12589
9221
11078
24793
27420
2000
20147
22379
11238
12594
9232
11089
24807
27434
2200
20161
22392
11243
12599
9241
11098
24818
27445
aC, B, and S stand for corn, beans, and sorghum, respectively,
b. „ -
In quetzales per year.

Table A-29.-~Farm size-quantity relationships for the associations graphed
in Figure 9
a
A.b
i
C-B
C-B
C-B
C-S
C-B-S
1
5
6
6
6
qm
aT
aT
qt
qm
nT
qt
0.05
4745
6977
3534
4900
4032
5889
9203
11830
-432
2313
0.10
8440
10672
5718
7074
6830
8687
14440
17067
1560
4305
0.25
13418
15650
8316
9672
10292
12149
19474
22101
6156
8901
0.50
16300
18532
9663
11019
12154
14011
21884
24511
11074
13819
0.75
17512
19444
10199
11555
12909
14766
22808
25435
14194
16939
1.00
18180
20412
10487
11843
13317
15174
23297
25924
16350
19095
1.25
18602
20834
10667
12023
13574
15431
23600
26227
17928
20673
1.50
18894
21126
10790
12146
13749
15606
23805
26432
19134
21879
1.75
19107
21339
10880
12236
13877
15734
23954
26581
20085
22830
2.00
19270
21502
10948
12304
13974
15831
24067
26694
20854
23599
2.25
19398
21630
11001
12357
14051
15908
24155
26782
21489
24234
2.50
19502
21734
11044
12400
14113
15970
24226
26853
22023
24768
2.75
19588
21820
11080
12436
14164
16021
24285
26912
22477
25222
3.00
19660
21892
11109
12465
14206
16063
24334
26961
22868
25613
3.25
19721
21953
11135
12491
14243
16100
24375
27002
23209
25954
3-50
19774
22006
11156
12512
14274
16131
24411
27038
23508
26253
aC, B, and S stand for corn, beans, and sorghum, respectively.
b|n hectares.

Table A-
30.—Price
-quantity
relationships for
the assoc
iations
graphed
in Figure
10a
p.b
i
C
-B
C-B
c-
B
C
-s
c
-B-S
1
5
6
6
6
aH
aT
qh
qm
qt
oM
4T
qm
qt
0.03
17521
19753
9523
10879
15882
17739
23791
26418
16377
19122
0.06
19615
21847
10489
11845
17353
19210
24358
26985
20822
23567
0.09
20415
22647
10850
12206
17900
18757
24552
27179
22802
25547
0.12
20838
23070
11040
12396
18185
20042
24651
27278
23922
26667
0.15
21099
23331
11156
12512
18360
20217
24710
27337
24642
27387
0.18
21276
23508
11235
12591
18478
20335
24750
27377
25144
27889
0.21
21405
23637
11291
12647
18563
20420
24778
27405
25514
28259
0.24
21502
23734
11334
12690
18628
20485
24800
27427
25799
28544
0.27
21578
23810
11368
12724
18678
20535
24816
27443
26024
28769
0.30
21639
23871
11395
12751
18719
20576
24830
27457
26206
28951
0.33
21690
23922
11417
12773
18752
20609
24840
27467
26537
29102
0.36
21732
23964
11436
12792
19780
20637
24850
27477
26484
29229
aC, B, and S stand for corn, beans, and sorghum, respectively.
In quetzales per kilogram.

Table A-31•Income-quant¡ty relationships for corngraphed in Figure 11
Y.3
i
1
3
4
5
6
qt
5T
qm
«T
qm
aT
qt
10
-831
552
-2108
217
-1527
225
-908
282
-1214
467
20
-449
934
-1898
427
-1312
441
-655
535
- 823
858
50
203
1586
-1299
1026
- 721
1032
- 32
1159
49
1730
100
687
2070
- 401
1924
110
1863
705
1895
933
2614
200
1060
2443
1097
3422
1367
3120
1587
2777
1830
3511
400
1302
2685
3278
5603
2954
4707
2430
3620
2557
4238
600
1394
2777
4791
7115
3915
5668
2837
4027
2871
4552
800
1442
2825
5900
8225
4560
6313
3077
4267
3047
4728
1000
1472
2855
6750
9075
5022
6775
3235
4425
3159
4840
1200
1492
2875
7420
9745
5370
7123
3348
4538
3236
4917
1400
1507
2890
7964
10289
5641
7394
3431
4621
3293
4974
1600
1518
2901
8413
10738
5858
7611
3496
4686
3336
5017
1800
1527
2910
8790
11115
6036
7789
3548
4738
3371
5052
2000
1533
2917
9111
11436
6184
7937
3590
4780
3399
5080
2200
1539
2922
9388
11713
6310
8063
3625
4815
3422
5103
a - ^ .
In quetzales per year.
VwO

Table A-32.--Farm size-quantity relationships for corn graphed in Figure 12
A.3
i
1
3
4
5
6
qm
aT
nH
aT
qm
qt
aT
qh
<¡T
0.05
-970
413
-2020
305
-1351
402
-570
620
1251
2932
0.10
-659
724
-1732
593
- 989
764
-108
1082
1842
3523
0.25
- 53
1330
- 956
1369
- 93
1660
764
1954
2327
4008
0.50
A59
1842
101
2426
974
2727
1482
2672
2520
4201
0.75
730
2113
942
3267
1717
3470
1855
3045
2589
4270
1 .00
898
2281
1628
3953
2264
4017
2083
3273
2624
4305
1.25
1012
2395
2197
4522
2683
4436
2237
3427
2645
4326
1.50
109¿4
2477
2677
5002
3015
4768
2348
3538
2659
4340
1.75
1157
2540
3088
5413
3285
5038
2432
3622
2670
4351
2.00
1206
2589
3443
5768
3508
5261
2498
3688
2677
4358
2.25
1246
2629
3753
6078
3695
5448
2551
3741
2683
4364
2.50
1278
2661
4026
6351
3855
5608
2594
3784
2688
4369
2.75
1305
2688
4269
6594
3993
5746
2630
3820
2692
4373
3.00
1328
2711
4485
6810
4114
5867
2661
3851
2695
4376
3.25
1348
2731
4680
7005
4219
5972
2687
3877
2698
4379
3.50
1366
2749
4856
7181
4313
6066
2710
3900
2701
4382
3.75
1381
2764
5016
7341
4397
6150
2730
3920
2703
4384
¿4.00
1394
2777
5162
7487
4472
6225
2747
3937
2705
4386
aln hectares.
vo
-c-

195
Table A-33.__Price-quantity relationships for corn graphed in Figure 13
p.a
1
Region
3
*4
qt
aH
qt
0.03
siso
8075
372*4
5**77
0.06
5986
8311
**336
6089
0.09
6067
8392
*<572
6325
0.12
6109
8*43*4
**697
6*450
0.15
613**
8*459
*477**
6527
0.18
6150
8*475
*4826
6579
0.21
6163
8*488
*486*4
6617
0.2*1
6172
8*497
**893
66*46
0.27
6179
850*4
*4916
6669
0.30
6184
8509
**93**
6687
0.33
6189
851*4
*49**9
6702
0.36
6193
8518
*4961
671**
0.39
6196
8521
**972
6725
0. *42
6199
852*4
*4981
673**
aln quetzales per kilogram.

196
Table A~34.— Income-quantity relationships for beans graphed
in Figure 14
Yia
Region
1
5
6
qh
qt
a"
qt
a11
qt
10
-172
167
-53
131
-274
112
20
- 52
287
41
225
-177
209
50
167
506
208
392
50
436
100
338
677
336
520
298
684
200
476
815
438
622
569
955
400
568
907
506
690
805
1191
600
604
943
532
716
912
1298
800
623
962
546
730
973
1359
1000
634
973
554
738
1013
1399
1200
642
981
560
744
1041
1427
14oo
648
987
564
748
1061
1447
1600
652
991
567
751
1077
1463
1800
656
995
570
754
1089
1475
2000
658
997
572
756
1099
1485
2200
661
1000
573
757
1108
1494
aln quetzales per year.

197
Table A-35---Income-quantity relationships for ricegraphed in Figure 15
Y.3
i
Region
4
5
6
a”
qt
on
qt
qm
qt
10
59
235
-22
247
-734
109
20
273
449
217
486
-627
216
50
815
991
876
1145
-319
524
100
1483
1659
1821
2090
155
998
200
2324
2500
3291
3560
981
1824
400
3173
3349
5223
5492
2266
3109
600
3601
3777
6436
6705
3220
4063
800
3858
4034
7268
7537
3957
4800
1000
4030
4206
7875
8144
4543
5386
1200
4154
4330
8336
8605
5020
5863
1400
4246
4422
8699
8969
5416
6259
1600
4318
4494
8992
9261
5750
6593
1800
4376
4552
9234
9503
6035
6878
2000
4423
4599
9437
9706
6282
7125
2200
4462
4638
9609
9878
6498
7341
a
In quetzales
per year.

198
Table A-36.—Farm size-quantity relationships for rice graphed in
Figure 16
A.3
1
Reg i on
5
6
qh
qt
qh
ttT
0.05
-165
104
692
1535
0.10
- 62
207
1613
2456
0.25
233
502
2996
3839
0.50
692
961
3882
4725
0.75
1114
1383
4276
5119
1 .00
1502
1771
4499
5342
1.25
1862
2131
4642
5485
1.50
2195
2464
4742
5585
1.75
2505
2774
4816
5659
2.00
2794
3063
4872
5715
2.25
3063
3332
4917
5760
2.50
3316
3585
4953
5796
2.75
3553
3822
4983
5826
3.00
3776
4045
5009
5852
3.25
3987
4256
5030
5873
3.50
4185
4454
5049
5892
0
In hectares.

199
Table A-37.--Farm size-quantity relationships for wheat graphed in
Figure 17
A.a
i
Reg ion
1
6
aH
qt
aH
ttT
0.05
100
415
36
62
0.10
382
697
97
123
0.25
863
1178
273
299
0.50
1214
1529
543
569
0.75
1382
1697
788
814
1.00
1482
1797
1012
1038
1 .25
1547
1862
1217
1243
1.50
1593
1908
1406
1432
1.75
1628
1943
1579
1605
2.00
1654
1969
1740
1766
2.25
1675
1990
1890
1916
2.50
1693
2008
2029
2055
2.75
1707
2022
2158
2184
3-00
1719
2034
2280
2306
3.25
1730
2045
2393
2419
3-50
1739
2054
2500
2526
aln hectares.

REFERENCES
1. Abbott, J.C. "Marketing Issues in Agricultural Development
Planning.," Markets and Marketing in Developing Economies,
eds., Moyer R., and S.C. Hollander. Homewood, Illinois:
Richard D. Irwin, 1968.
2. . "The Development of Marketing Institutions.,"
Agricultural Development and Economic Growth, eds., H.
Southworth and B.F. Johnston. N.Y.: Cornell University
Press, 1967-
3- _. "The Role of Marketing in the Development of
Backward Agricultural Economies," Marketing and Economic
Development-Readings in Agribusiness Research, ed., Clarence
J. Miller. Lincoln, Nebraska: University of Nebraska Press,
1967.
k. Andrew, Chris 0. "Marketing Needs of Small Farmers under Multiple
Cropping Systems." Staff Paper 3, Food and Resource Economics
Department, University of Florida, April, 1975-
5. Andrew, Chris 0., et al. Problemas de Mercadeo y Producción del
Campes i no. Boletín Técnico No. 10, Instituto Colombiano
Agropecuario, Ministerio de Agricultura, March, 1971.
6. Bardhan, Kalpana. "Price and Output Response of Marketed Surplus
of Foodgrains: A Cross-Sectional Study of Some North Indian
Villages." American Journal of Agricultural Economics 52
(1970): 51-61.
7. Bateman, Merrill J. "Supply Relations for Perennial Crops in
the Less Developed Areas." Subsistence Agriculture and
Economic Development, ed. , C.R. V/harton, Jr. Chicago,
Illinois: Aldine Publishing Co., 1969-
8. Bauer, P.T., and B.S. Yamey. "A Case Study of Response to Price
in an Underdeveloped Country." The Economic Journal 69
(1959): 800-805.
9- Behrman, Jere R. "Price Elasticity of the Marketed Surplus of a
Subsistence Crop." Journal of Farm Economics kQ (1966):
875-893.
200

201
10. . "Supply Response and the Modernization of Peasant
Agriculture: A Study of Four Major Annual Crops in Thailand."
Subsistence Agriculture and Economic Development, ed., C.R.
Wharton, Jr. Chicago, Illinois: Aldine Publishing Co., 1969-
11 . . Supply Response in Underdeveloped Agriculture.
Amsterdam: North-Hoi 1 and Publishing Co., 1968.
12. Biggs, Huntley H., and R.L. Tinnermeier, eds. Smal1 Farm Agricul¬
tural Development Problems. Colorado: Colorado State Univer-
sity, 197-4
13- Bonnen, J.T., C.K. Eicher, and A. Allan Schmid. "Marketing in
Economic Development." Agricultural Market Analysis-Develop¬
ment, Performance, Process, ed., V.L. Soreson, pp. 35~49,
Michigan: Michigan State University Press, 1964.
14. Chaturvedi, J.N. The Theory of Marketing in Underdeveloped
Countries, Chapter 10. Delhi, India: Kitab Mahl Publishers,
1959-
15- Chinn, Dennis L. "The Marketed Surplus of a Subsistence Crop:
Paddy Rice in Taiwan." American Journal of Agricultural
Economics 58 (1976): 583-587.
16. Collins, N.R., and R.H. Holton. "Programming Changes in Marketing
in Planned Economic Development." Agriculture in Economic'
Development, eds., C. Eicher and L. Witt, pp. 359“369*
N.Y.: McGraw-Hill Book Company, 1964.
17- Coriseo, Amalia. Estudio de la Comunidad de Santo Domingo
Xenacoj, Departmento de Sacatep^quez. Guatemala: Socio-
economia Rural, 1CTA. In Process.
18. Currie, Lauchlin. "Marketing Organization for Underdeveloped
Countries." Markets and Marketing in Developing Economies,
eds., Moyer, Reed and S.C. Hollander. Homewood, Illinois:
Richard D. Irwin, 1968.
19. Daines, Samuel R. Guatemala Farm Policy Analysis--The Impact of
Small-Farm Credit on Income, Employment, and Food Production.
Washington, D.C.: Agency for International Development,
April 1975.
20. Dean, Edwin R. "Economic Analysis and African Response to Price."
Journal of Farm Economics 47 (1965): 402-409-

202
21. . The Supply Responses of African Farmers: Theory
and Measurement in Malawi. Amsterdam: North Holland
Publishing Co., 1966.
22. Diario La Tarde. Año VI, No. 1614, Guatemala, Martes 20 de Enero
de 1976.
23. Dixit, A.K. "Marketable Surplus and Dual Development." Journal
of Economic Theory 1 0969): 203-219-
24. Dombrcwski, John, et^ a_l_. Area Handbook for Guatemala. DA Pam
550-78. Washington, D.C.: The American University, March
1970.
25- Dorner, Peter., ed. "Policy Implications." Land Reform in Latin-
America-Issues and Cases. Madison: Land Economics Monograph
No. 3, University of Wisconsin, 1971.
26. Dorner, Peter and Don Kanel. "The Economic Case for Land Reform:
Employment, Income Distribution, and Productivity." Land
Reform in Lat?n-America-~1ssues and Cases, ed., Peter Dorner,
pp. 41-56. Madison:Land Economics Monograph No. 3,
University of Wisconsin, 1971.
27. Dovring, Folke. "The Share of Agriculture in a Growing Population
Agriculture in Economic Development, eds., C. Eicher and L.
Witt, pp. 78-98. N.Y.: McGraw-Hill Book Co., 1964.
28. Drucker, Peter F. "Marketing and Economic Development." The
Environment of Marketing Behavioi—Selections from the
Literature, eds., R.J. Holloway and R.S. Hancock, pp. 333“
338. N.Y.: John Wiley & Sons, 1964.
29. Dubey, Vinod. "The Marketed Agricultural Surplus and Economic
Growth in Underdeveloped Countries." Economic Journal 73
(1963): 689-702.
30. Durbin, J. and G.S. Watson. "Testing for Serial Correlation in
Least-Squares Regression, I." Biometrika 37 (1949):
409-428.
31. Falcon, Walter P. "Factor Response to Price in a Subsistence
Economy: The Case of V/est Pakistan." American Economic
Review 54 (1964): 580-591.
. "The Green Revolution: Generation of Problems.
American Journal of Agricultural Economics 52 (1970): 698-
710.
32.

203
33- Fisher, Franklin M. "A Theoretical Analysis of the Impact of
Food Surplus Disposal on Agricultural Production in Recipient
Countries." Journal of Farm Economics k$ (1963): 863“875-
3A. Fletcher, L.B. "Commodity Markets and Market ing ]Economic
Development of Agriculture--The Modernization of Farming,
ed., Ames, Iowa: Iowa State University Press, 1965*
35- Fletcher, L.B., et al . Guatemala's Economic Development-~The
Roleof Agriculture. Ames, Iowa: The Iowa State University
Press, 1970.
36. Gaitskell, Arthur. "Importance of Agriculture in Economic Develop¬
ment." Economic Development of Tropical Agriculture, ed.,
W.W. McPherson. Gainesville, Florida: University of
Florida Press, 1968.
37.
George, P.S., and G.A. King. Consumer Demand for Food
in the United States with Projections for 1980.
University of California, Division of Agricultura
Giannini Foundation Monograph 26, March 1971.
Commodities
California:
1 Sciences,
38. Ghoshal, Animesh. "The Price Responsiveness of Primary Producers:
A Relative Supply Approach.1.1 American Journal of Agricultural
Economics 57 (1975): 116—118.
39* Haessel, Walter. "The Price and Income Elasticities of Home
Consumption and Marketed Surplus of Foodgrains." American
Journal of Agricultural Economics 57 (1975): 111-115-
kO. Harrison, Kelly. Agricultural Market Coordination in the Economic
Development of Puerto Rico. Ph.D. Dissertation, Michigan
State University, 1966.
Al. . "Approaches to Integration of Rural Urban Food
Marketing Systems in Latin America." Paper presented to the
Agricultural Development Council Workshop on Agricultural
Marketing in Developing Countries, Lexington, Kentucky,
October 7"9, 1971.
k2. . Development, Unemployment, and Marketing in
Latin America. Occasional Paper No. 2, Latin American
Studies Center, Michigan: Michigan State University, April
1972.
A3. Harrison, Kelly and Kenneth Shivedel. "Marketing Problems
Associated with Small Farm Agriculture." Report on an ADC/RTN
Seminar held at Michigan State University, June 7-8, 197A.
N.Y.: The Agricultural Development Council, Inc., November 197A.

204
44. Harrison, Ke 1 1 y et_ aj_. Improving Food Marketing Systems in Develop¬
ing Countries: Experiences from Latin America. Research
Report Ho. 6, Latin American Studies Center, East Lansing,
Michigan: Michigan State University, November 1974.
45. Heady, Earl and Leo Mayer. "Balancing the Flow of Resources
between Production and Marketing." The Marketing Challenge--
Distributing Increased Production in Developing Nations,
ed. Martin Kriesberg. Wash i ngton, D.C.: IJ.S. Department
of Agriculture, Foreign Economic Report 7, December 1970.
46. Heady, Earl 0. "Processes and Priorities in Agricultural Develop-
ment." Economic Development of Tropical Agriculture,
ed. W.W. McPherson. Ghinesville, Florida: University of
Florida Press, 1968.
47. Hill, George W. , and Mi Collas. The Minifundia Economy and Society
of the Guatemalan Highland Indian. Wisconsin: University
of Wisconsin, Land Tenure Center, Report No. 30, July 1968.
48. Hirschman, Albert 0. The Strategy of Economic Development. New
Haven, Conn.: Yale University Press, 1966.
49. Holloway, R.J. and R.S. Hancock., eds. The Environment of Marketing
Behayior--Selections from the Literature. N.Y.: John Wiley S
Sons, Inc., 1964.
50. Hussain, Syed M. "A Note on Farmer Response to Price in East
Pakistan." Pakistan Development Review 4 (1964): 93~106.
51. IBRD. The Economic Development of Guatemala. Washington, D.C.:
International Bank for Reconstruction and Development, 1951.
52. ICTA. "Evaluación del Trabajo del ICTA en la Cooperativa Santa
Lucia. R.L., Departamento de Sololá' y con el Programa de
Vecinos Mundiales, Depto. de Chima1tenango." Guatemala:
ICTA, Socioeconomía Rural, August 1975- Mimeo.
53- • "Programa de Socioeconomía Rural." Guatemala: ICTA.
Mimeo.
54. INDECA. Algunos Aspectos de Producción y Comercialización de
Maíz y Frijol en Varias Regiones del País. Guatemala:
INDECA, June 1971.
_. Comercio Internacional y Noticias de Mercadeo Interno
de Productos Agrícolas. Guatemala: INDECA, División
Técnica, Quarterly Issues.
55.

205
56- . Noticias de Mercadeo de Productos AgrTcolas. Guatemala:
INDECA, Depto de Investigación, Capacitación y Extensfón de
Mercadeo, Monthly Issues.
57- Johnson, Glenn L. "Factor Markets and Economic Development."
Economic Development of Tropical Agriculture, ed. W.W. r
McPherson. Gainesville, Florida: University of Florida
Press, 1968.
58. Johnston Bruce F. , and John V/. Mel lor. "The Role of Agriculture
in Economic Development." Leading Issues in Developing
Economics, ed. Gerald M. Meier, pp. 291-297- N.Y.: Oxford
University Press, 1964.
59. Johnston, J. Econometric Methods. N.Y.: McGraw-Hill Book
Company, Inc., 1972.
60. Kahlon, A.S., and H.N. Dwivedi. "Interrelationships Between
Production and Marketable Surplus." Asian Economic Review 5
(1963): 471-487.
61. Khan, A.R., and .A.H..M,. Nuruddin Chowdhury. "Marketable Surplus
Function: A Study of the Behavior of West Pakistan Farmers."
Pakistan Development Review 2 (1962): 354-376.
62. Khan, M.H. "Real Effects of Foreign Surplus Disposal in Under¬
developed Economies: Comment." Quarterly Journal of
Economics 78 (1964): 348-349-
63. Khatkhate, Deena R. "Some Notes on the Real Effects of Foreign
Surplus Disposal in Underdeveloped Economies." Quarter 1y
Journal of Economics 76 (1962): 186-196.
64. King, Richard A. "Product Markets and Economic Development."
Economic Development of Tropical Agriculture, ed. W.W.
McPherson. Gainesville, Florida: University of Florida
Press, 1968.
65. Kmenta, Jan. Elements of Econometrics. N.Y.: The Macmillan
Company, 1971-
66. Kriesberg, Martin., ed. The Marketing Chailenge--Distributing
Increased Production in Developing Nations. Washington, D.C.
U.S. Department of Agriculture, Foreign Economic Development
Report 7, December 1970.
67. Kriesberg, Martin and Howard Steele. Improving Marketing Systems
in Developing Countries—An Approach to Identifying Problems
and Strengthening Technical Assistance. Washington, D.C.:
U.S. Department of Agriculture, Foreign Agricultural
Economic Report No. 93, February 1972.

206
68. Krishna, Raj. "Agricultural Price Policy and Economic Development."
Agricultural Development and Economic Growth, eds., H.
Southworth and B.F. Johnston, pp*! 497-5^7- N . Y. : Cornel 1
University Press, 1967-
69. . "A Note on the Elasticity of the Marketable Surplus
of a Subsistence Crop." Indian Journal of Agricultural
Economics 17 (1962): 79“84.
70. . "Farm Supply Response in India-Pakistan : A Case
Study of the Punjab Region." Economic Journal 73 (1963): 477“487•
71. . "The Marketable Surplus Function for a Subsistence
Crop." Economic Weekly Annual Volume (1965): 309“320.
72. Krishran, T.N. "The Marketed Surplus of Food Grains: Is It
inversely Related to Price?" Economic Weekly 17 (1965):
325-328.
73* Larzelere, Henry. "Cooperatives in Agricultural Marketing."
Agricultural Market Analysis-Development, Performance,
Process, ed., V.L. Soreson, pp. 205_2l6. Michigan: Michigan
State University Press, 1964.
74. Lewis, W. Arthur. "Economic Development With Unlimited Supplies
of Labour." The Manchester School, May 1954.
75- MacDonald, Charles et_ aj_. Agr i cu 1 ture-Guatema 1a-Statistical
Working Document #18--A Close Look at Some Statistics from
the 1974 Guatemala Small Farm Survey. Washington, D.C.:
Sector Analysis Division, Bureau for Latin America, Agency
for International Development, January 1975-
76. Mangh'as ,, M. , Aida E. Recto, and V.W. Ruttan. "Price and Market
Relationships for Rice and Corn in the Philippines."
Journal of Farm Economics 48 (1966): 685“703.
77- Mathur, P.N., and H. Ezekiel. "The Marketable Surplus of Food
and Price Fluctuations in a Developing Economy." Kyklos 14
(1961): 396-406.
78. Medani, A. I. "Elasticity of the Marketable Surplus of a Subsis¬
tence Crop at Various Stages of Development." Economic
Development and Cultural Change 23 (1975): 421-429-
Mehren, George L. "Market Organization and Economic Development."
Journal of Farm Economics 4l (1959): 1307"1315-
79-

207
80. Meier, Gerald M., ed. Leading Issues in Development Economics.
N.Y.: Oxford University Press, 1964.
81. Mel lor, John W. "The Agricultural Marketing System and Price
Stabilization Policies." Ithaca, N.Y.: Cornell University
Press, Staff Paper No. 26, December 1970.
82. Miracle, Marvin P. "Subsistence Agriculture: Analytical Problems
and Alternative Concepts." American Journal of Agricultural
Economics 50 (1968): 292-310.
83. Moyer, Reed. "Marketing in Economic Development." East Lansing,
Michigan: Michigan State University, institute for inter¬
national Business Studies, Occasional Paper No. 1, 1965-
84. Moyer, R., and S.C. Hollander., eds. Markets and Marketing in
Developing Economies. Homewood, Illinois: Richard D. Irwin,
Inc., 1968.
85. Mubyarto. "The Elasticity of the Marketable Surplus of Rice in
Indonesia: A Study in Java-Madura." Ph.D. Dissertation,
Iowa State University, 1965*
86. Mueller, Willard F. "Some Market Structure Considerations
in Economic Development." Journal of Farm Economics 41
(1959): 414-425.
87. Narain, Dharm. Distribution of the Marketed Surplus of Agri-
cultural Pro~duce by Size-Level of Holding in India l96u-9'l •
Delhi,Bombay:Asia Publishing House, 1961.
88. Nason, Robert W., ed. The Role of Food Marketing in the Economic
Development of Puerto Rico--Seminar Summary. East Lansing,
Michigan: Michigan State University, Latin American Studies
Center, 1966.
89. Nicholls, William H. "The Place of Agriculture in Economic
Development." Agriculture in Economic Development, eds.,
C. Eicher and L. Witt. N.Y.: McGraw-Hill Book Co., 1964.
90. Oldenstadt, D., and David Call. "Group Action in Agricultural
Marketing." Agricultural Market Analysis — Development,
Performance, Process, ed. V.L. Soreson. Michigan: Michigan
- State University, 1964.
91. Olson, R.O. "Discussion: Impact and Implications of Foreign
Surplus Disposal in Underdeveloped Economies." Journal of
Farm Economics 42 (i960): 1042-1045-

208
92. 0'Quinn, Floyd. General Working Document iff50~~Descriptive Tables
of Guatemala Small Farm Survey. Washington, D.C.: Sector
Analysis Division, Bureau for Latin America, Agency for
International Development, May 1975.
93- Papanek, Gustav F. "Development Problems Relevant to Agriculture
Tax Pol icy." Papers and Proceedings of the Conference on
Agricultural Taxation and Economic Development, pp. 193-196.
Cambridge, Mass.: Harvard Law School, 195*1.
9*1. Patrick, George F. , et al . , eds. Small-Farm Agriculture: Studies
in Developing Nations. Indiana: Purdue University, Agri¬
cultural Experiment Station, Department of Agricultural
Economics, September 1975-
95- Pearson, Harry W. "The Economy Has Ho Surplus: Critique of a
Theory of Development." Trade and Markets in the Early
Empi res, ed. K. Polanyi, C.M. Arensberg, and H.W. Pearson,
p. 339- Glencoe, Illinois: Free Press, 1957•
96. Perrin, Richard and Don Winkelmann. "Impediments to Technical
Progress on Small versus Large Farms." American Journal of
Agricultural Economics 58 (1978): 888-89**•
97. Prebisch, Raul. "Commercial Policy in the Underdeveloped Countries."
Leading Issues in Development Economics, ed. Gerald M.
Meier, pp. 286-289. N.Y.: Oxford University Press, 196*1.
98. Proenza, Francisco J. "Producción de Mafz en Guatemala —
Diferencias Tecnológicas, AdopcTon de Insumos Modernos y
el Programa de Asistencia al Pequeño Agricultor." Washington,
D.C.: U.S.D.A.-E.R.S., December 1975, In Process.
i
99- Recto, Aida E. "Price and Market Relationships for Corn in the
Philippines." Unpublished Master's thesis, University of
the Philippines, 1965-
100. Reynolds, A.E. "Effects of Technology on Marketing." The Environ¬
ment of Marketing Behavioi—Selections from the Literature,
eds. , R. J . Hoi loway and R.S. Hancock, pp"! 1 5*1” 157• N.Y. :
John Wiley & Sons, 196*1.
101. Ricardo, José M. General Working Document #51--Eva 1uation of
Technical Assistance Impacts on Small Farmers' Performance
of Guatemala Small Farm Survey. Washington, D.C.: Sector
Analysis Division, Bureau for Latin America, Agency for
International Development, June, 1975-

209
102. Riley, Harold. "Evaluation of Marketing Systems in Latin America."
A paper presented to the Markets and Trade and Economic
Development Workshop, North Carolina State University,
Raleigh, North Carolina, February 20, 1968.
103. . "Improving Internal Marketing Systems as Part
of National Development Systems." Michigan: Michigan
State University, Latin American Studies Center, Occasional
Paper No. 3, May 1972.
10*4. . Market Coordination in the Development of the
Cauca Valley Region—Colombia. East Lansing, Michigan:
Michigan State University, Latin American Studies Center,
Research Report No. 5, March 1970.
105. Riley, Harold et_ a_K Food Marketing in the Economic Development
of Puerto Rjco. East Lansing, Michigan: Michigan State
University, Latin American Studies Center, Research Report
No. 4, July 1970.
106. Robertson, Thryel e et_ jU. Agr i cul ture--Guatemal a—Methodolog i cal
Working Document #51. Washington, D.C.: Sector Analysis
Division, Bureau for Latin America, Agency for (nternational
Development, February 1975.
107. Ruano, Sergio. "El Altiplano: ¿Una Zona Maicera en el Futuro?."
Guatemala: ICTA, Socioeconomfa Rural. Typed.
108. Schultz, Theodore W. Transforming Traditional Agriculture. New
Haven, Conn.: Yale University Press, 1969.
109. • "Value of U.S. Farm Surpluses to Underdevel¬
oped Countries." Journal of Farm Economics 42 (i960):
1019-1030.
110. Scott, C.D. Some Problems of Marketing Among Small Peasant
Proprietors in Chile. Madison, Wisconsin: University of
Wisconsin, Land Tenure Center, June 1974.
111. Sen, S.R. "Impact and Implications of Foreign Surplus Disposal
on Underdeveloped Economies--The Indian Perspective."
Journal of Farm Economics 42 (i960): 1031-1042.
112. Shaw, Arch W. "Some Problems in Market Distribution." The
Environment of Marketing Behavioi—Selections from the
Literature, eds., R.J. Holloway and R.S. Hancock, pp. 5-9<
N.Y.: John Wiley & Sons, 1964.
113- Stern, R.M. "The Price Responsiveness of Egyptian Cotton
Producers." Kyklos 12 0959): 375-384.

210
11*4. Stern, R.M. "The Price Responsiveness, of Primary Producers."
Review of Economics and Statistics *1*4 (.1962): 202-207.
115- The Agricultural Development Council. "Marketing Institutions
and Services for Developing Agriculture." Report on an
ADC/RTN Seminar held in Washington, D.C., September 10-12,
197*4. N.Y.: The Agricultural Development Council, Inc.,
July 1975.
116. Toquero, Zenaida, Bart Duff, Teresa Anden, and Yujiro Hayami.
"Marketable Surplus Functions for a Subsistence Crop:
Rice in the Philippines." American Journal of Agricultural
Economics 57 (1975): 705-709-
117- U.S. Department of Agriculture. Agricultural Trade of the
Western Hem?sphere--A Statistical Review, 1963~73^
Washington, D.C,: U.S. Department of Agriculture, E.B.S.
Statistical Bulletin No. 5^6, July 1975-
118. Waugh, Robert K. The Institute of Agricultural Science and
Technology of Guatemala (.Instituto de Ciencia y Tecnología
Agrícolas) ICTA--Four Years of History. Guatema1 a: ¡"CTA,
September 1975-
119- Wharton Jr,, Clifton R. Subsistence Agriculture and Economic
Development. Chicago, Illinois: Aldine Publishing Co.,
1969.
120. Wiens, Thomas B. "Peasant Risk Aversion and Allocative Behavior:
A Quadratic Programming Experiment." American Journal of
Agricultural Economics 58 (1976): 629-635-
121. Witt, L., and Carl Eicher. The Effects of United States Agri¬
cultural Surplus Disposal Programs on Recipient Countries.
East Lansing, Michigan: Michigan State University,
Department of Agricultural Economics Research Bulletin
No. 2, 1964.
122. Zarembka, P. "Marketable Surplus and Growth in the Dual Economy."
Journal of Economic Theory 2 (1970): 107-121.

BIOGRAPHICAL SKETCH
Jose Alvarez was born in Oriente, Cuba, on December 10, 19^0.
He attended Law School in Oriente University and Havana University.
In February, 1969, he came to the United States. He received his
Bachelor of Arts degree with a major in economics, with honors, from
the University of Florida, in December, 1971, and his Master of
Science in Agriculture in August, 197^- He is now a candidate for
the degree of Doctor of Philosophy.
He is a member of the American Agricultural Economics Associa¬
tion, the American Economic Association, the Southern Agricultural
Economics Association, Omicron Delta Epsilon, and the Society for
International Development.
He is married to the former Mercy Fernández and has two children,
Mercita and Ricardo José".

I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the
degree of Doctor of Philosophy.
C.O. Andrew, Chairman
Associate Professor of Food and
Resource Economics
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the
degree of Doctor of Philosophy.
It
Leo Polopolus
Professor of Food and Resource
Economics
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the
degree of Doctor of Philosophy.
R.W. Ward
Associate Professor of Food and.
Resource Economics
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, as a dissertation for the
degree of Doctor of Philosophy.
Graduate Research Professor of Food
and Resource Economics

I certify that I have read this study, -and that in my opinion it
conforms to acceptable standards of scholarly presentation and is
fully adequate, in scope and quality, 'as a/d i ssji.i^t-qti^n for the
degree of Doctor of Philosophy.
. J. Ca pvaja I
Ass i s tnVrt "P/of essor for the Center
fóV L^tin American Studies'
This dissertation was submitted to the Graduate Faculty of the
College of Agriculture and to the Graduate Council, and was
accepted as partial fulfillment of the requirements for the degree
of Doctor of Philosophy.
June 1977
Dean, Graduate School